%{search_type} search results

• Intro
• Contents
• Preface
• AI for Software Design
• 1. Interweaving AI and Behavioral Programming Towards Better Programming Environments
• 1.1 Introduction
• 1.2 Preliminaries
• 1.2.1 Behavioral and Scenario-Based Programming
• 1.2.2 Model-Driven Engineering
• 1.2.3 Search-Based Software Engineering (SBSE)
• 1.2.4 Evolutionary Computation
• 1.3 The Proposed Approach
• 1.4 Sandboxing
• 1.5 State Space Exploration
• 1.6 Heuristics and Smart Exploration
• 1.7 Examples
• 1.7.1 StarCraft
• 1.7.2 Robocode
• 1.7.3 RoboSoccer
• 1.8 Conclusions
• References

• 2. AI Techniques for Software Requirements Prioritization
• 2.1 Introduction
• 2.2 Early Requirements Engineering
• 2.3 Minimum Viable Products
• 2.4 Basic Release Planning
• 2.5 Integrated Release Planning
• 2.6 Stakeholder Recommendation
• 2.7 Research Issues
• 2.8 Conclusions
• Acknowledgment
• References
• Agent-Based Software Programming
• 3. Social Commitments for Engineering Interaction in Distributed Systems
• 3.1 Introduction
• 3.2 Background on Goal Distribution and Coordination
• 3.3 Background on Social Commitments
• 3.4 Business Artifacts with Social Commitments

• 3.5 Patterns for Programming Agents with Social Relationships
• 3.6 The Hiring Process Scenario
• 3.7 Conclusions
• References
• 4. Intelligent Agents are More Complex: Initial Empirical Findings
• 4.1 Introduction
• 4.2 Background
• 4.3 Software Project Data Collection and Curation
• 4.3.1 Data Sources
• 4.3.2 Automatic Data Harvesting
• 4.3.3 The Measurement Pipeline
• 4.4 Statistical Analysis
• 4.5 Machine Learning Analysis
• 4.6 Discussion
• 4.7 The Big Picture and Future Directions
• References
• AI for Software Development

• 5. Sequence-to-Sequence Learning for Automated Software Artifact Generation
• 5.1 Introduction
• 5.2 Preliminary Knowledge of Seq2Seq Learning
• 5.2.1 Recurrent Neural Network (RNN)
• 5.2.2 Encoder-Decoder Model
• 5.2.3 Attention Mechanism
• 5.2.4 Evaluation Metrics for Software Artifact Generation
• 5.3 Automated Generation of Code Comments
• 5.3.1 Problem and Challenges
• 5.3.2 The Seq2Seq Model: Hybrid-DeepCom
• 5.3.2.1 Capture Syntactic Information of Source Code
• 5.3.2.2 Fuse Lexical and Syntactic Information
• 5.3.2.3 Reduce OOV tokens
• 5.3.3 Dataset
• 5.3.4 Evaluation

• 5.4 Automated Generation of Pull Request Descriptions
• 5.4.1 Problem and Challenges
• 5.4.2 The Seq2Seq Model: PRSummarizer
• 5.4.2.1 Pointer Generator
• 5.4.2.2 RL Loss
• 5.4.3 Dataset
• 5.4.4 Evaluation
• 5.5 Automated Generation of App Review Responses
• 5.5.1 Problem and Characteristics
• 5.5.2 The Seq2Seq Model: RRGen
• 5.5.2.1 Integrating High-Level Attributes
• 5.5.2.2 Integrating Keywords
• 5.5.3 Dataset
• 5.5.4 Evaluation
• 5.6 Case Study Comparison
• 5.7 Challenges and Opportunities
• 5.7.1 Challenges
• 5.7.2 Opportunities
• 5.8 Summary
• References

Software is an integral part of our lives today. Modern software systems are highly complex and often pose new challenges in different aspects of Software Engineering (SE).Artificial Intelligence (AI) is a growing field in computer science that has been proven effective in applying and developing AI techniques to address various SE challenges.This unique compendium covers applications of state-of-the-art AI techniques to the key areas of SE (design, development, debugging, testing, etc).All the materials presented are up-to-date. This reference text will benefit researchers, academics, professionals, and postgraduate students in AI, machine learning and software engineering.
(source: Nielsen Book Data)

• Combined Intelligent and Adaptive Optimization in End Milling of Multi-layered 16MnCr5/316L
• Jaya: A New Meta-heuristic Algorithm for the Optimization of Braced Dome Structures
• Damage Detection of Truss Employing Swarm-Based Optimization Techniques
• Multi-objective Optimization of Wire-Electric Discharge Machining Process Using Multi-objective Artificial Bee Colony Algorithm
• Optimization of Process Parameters in Pulsed Electrochemical Honing Process Using Evolutionary Algorithms
• Modeling and Simulation of Huge AC Power Network for Optimization of Corona Power Loss Through TLBO Algorithm
• Optimization of Water Distribution Networks Using Cuckoo Search Algorithm
• GA-Based Hybrid Approach to Solve Fuzzy Multi-objective Optimization Model of Multi-application-Based COTS Selection Problem
• Optimization of Parameters for Steel Recycling Process by Using Particle Swarm Optimization Algorithm
• Modeling 3D WSN to Maximize Coverage Using Harmony Search Scheme
• An Efficient Jaya Algorithm for Multi-objective Permutation Flow Shop Scheduling Problem
• Multi-objective Optimization of EDM Process Parameters Using Jaya Algorithm Combined with Grey Relational Analysis
• Application of Fuzzy Integrated JAYA Algorithm for the Optimization of Surface Roughness of DMLS Made Specimen: Comparison with GA
• Comparative Analysis of Fruit Categorization Using Different Classifiers
• Design Optimization of Plate-Fin Heat Exchanger by Using Modified Jaya Algorithm
• Prediction of Factor of Safety For Slope Stability Using Advanced Artificial Intelligence Techniques
• The Use of Grey Relational Analysis to Determine Optimum Parameters for Plasma Arc Cutting of SS-316L
• Jaya Algorithm Based Intelligent Color Reduction
• Tooth Profile Optimization of Helical Gear with Balanced Specific Sliding Using TLBO Algorithm
• Optimization of Nanofluid Minimum Quantity Lubrication (NanoMQL) Technique for Grinding Performance Using Jaya Algorithm
• Performance Evaluation of Jaya Optimization Techniquefor the Production Planning in a Dairy Industry
• Multi-objective Optimization in WEDM of Inconel 750 Alloy: Application of TOPSIS Embedded Grey Wolf Optimizer
• Experimental Investigations and Selection of Solid Lubricant Assisted Lubrication Strategy in Machining with the Use of PROMETHEE
• BPSO-Based Feature Selection for Precise Class Labeling of Diabetic Retinopathy Images
• Dynamic Analysis and Life Estimation of the Artificial Hip Joint Prosthesis
• Sarkar Modeling Elastic Constants of Keratin-Based Hair Fiber Composite Using Response Surface Method and Optimization Using Grey Taguchi Method
• A Decennary Survey on Artificial Intelligence Methods for Image Segmentation
• Air Quality Assessment Using Fuzzy Inference Systems
• Optimization of Water Releases from Ukai Reservoir Using Jaya Algorithm
• Design of Antenna Arrays Using Chaotic Jaya Algorithm
• Optimization of Friction Drilling Process by Response Surface Methodology
• Optimization of Parameters in Friction Stir Welding of AA6101-T6by Taguchi Approach
• Evolutionary Optimization in Master Production Scheduling: A Case Study
• Optimal Irrigation Planning in the Eastern Gandak Project Using Linear Programming---A Case Study
• Optimization of Squeeze Casting Process Parameters to Investigate the Mechanical Properties of AA6061/Al2O3/SiC Hybrid Metal Matrix Composites by Taguchi and Anova Approach
• Parametric Optimization of Electrochemical Machining Process Using Taguchi Method and Super Ranking Concept While Machining on Inconel 825
• Dependency of Bead Geometry Formation During Weld Deposition of 316 Stainless Steel Over Constructional Steel Plate
• Performance Assessment of Inter-Digital Capacitive Structure-Finite Element Approach --MADM-Based Approach for Selection of Welding Process for Aluminum Tube Manufacturing
• Screening of Organic Brake Pad Materials Using MADM Technique
• Selection of Coating and Nitriding Process for AISI 4140 Steel Material to Enhance Tribological Properties
• Risk-Pooling Approach in Inventory Control Modelfor Multi-products in a Distribution Network Under Uncertainty
• Optimization of Magnetic Abrasive Finishing Process Using Principal Component Analysis
• Dynamic Distribution Network Expansion Planning Under Energy Storage Integration Using PSO with Controlled Particle Movement
• Development of Plant Layout for Improving OrganizationalEffectiveness by Hybridizing GT, TOPSIS and SLP
• Optimization of Process Parameters Using Hybrid Taguchiand VIKOR Method in Electrical Discharge Machining Process
• Multi-response Optimization of Burnishing of Friction-WeldedAA6082-T6 Using Principal Component Analysis
• Design Optimization of Helicopter Rotor with Trailing-Edge Flaps Using Genetic Algorithm
• Statistical Model for Spot Welding of Aluminum Alloy 6082T651Using an Interlayer
• Fuzzy Programming Technique for Solving Uncertain Multi-objective, Multi-item Solid Transportation Problem with Linear Membership Function
• Investigation of Influence of Process Parameters in Deep Drawing of Square Cup
• Selection of Machining Parameters in Ultrasonic Machining Process Using CART Algorithm
• PSF-Based Spectrum Occupancy Prediction in Cognitive Radio
• Hertzian Contact Stress Analysis in Roller Power Transmission One-Way Clutch by Using Finite Element Analysis Numerical Simulation and Experimental Study on Lightweight Mechanical Member
• Robust Analysis of T-S Fuzzy Controller for Nonlinear SystemUsing H-Infinity
• Adsorption of Crystal Violet Dye: Parameter Optimization Using Taguchi's Experimental Methodology
• Minimization of Springback in Seamless Tube Cold Drawing Process Using Advanced Optimization Algorithms
• Rao Integrated Production Planning and Scheduling for Parallel Production Lines
• Optimization of Surface Modification Phenomenon for P20+Ni DieSteel Using EDM with P/M Composite Electrode
• Optimization of Tool Wear and Surface Roughness of Hybrid Ceramic Tools
• Assessment of Viscosity of Coconut-Oil-Based CeO2/CuO Hybrid Nano-lubricant Using Artificial Neural Network
• Elimination of Nick Defect by Process Optimization for Input Shaft Reverse Gear Section
• Experimental Investigation of Cutting Parameters on Surface Roughness in Hard Turning of AISI 4340 Alloy Steel
• Experimental Study of Process Parameters on Finishing of AISI D3Steel Using Magnetorheological Fluid
• Evaluation of Aeration Efficiency of Triangular Weirs by Using Gaussian Process and M5P Approaches
• Performance Evaluation of Kaplan Turbine with Different Runner Solidity Using CFD
• Prediction of Occupational Risk at Workplace Using Artificial NeuralNetwork---A Case Study
• Quantification of Influence of Casting Variables for Minimizing HotSpot Area in T Junction by ANOVA and Taguchi Method
• Taguchi-Based Optimization of Machining Parameter in Drilling Spheroidal Graphite Using Combined TOPSIS and AHP Method
• Optimal Configuration of Viscous Dampers Connected to Adjacent Similar Buildings Using Particle Swarm Optimization
• Combined Economic Emission Dispatch Using Spider Monkey Optimization
• Solution of Non-convex Economic Dispatch Problems by Water Cycle Optimization
• Multi-objective Design Optimization of Shell-and-Tube Heat Exchanger Using Multi-objective SAMP-Jaya Algorithm
• An Improved Jaya Algorithm and Its Scope for Optimization in Communications Engineering
• Evaluation of TiN-Coated CBN Tools During Turning of Variable Hardened AISI 4340 Steel.

This book comprises select peer-reviewed papers presented at the International Conference on Advanced Engineering Optimization Through Intelligent Techniques (AEOTIT) 2018. The book combines contributions from academics and industry professionals, and covers advanced optimization techniques across all major engineering disciplines like mechanical, manufacturing, civil, automobile, electrical, chemical, computer and electronics engineering. Different optimization techniques and algorithms such as genetic algorithm (GA), differential evolution (DE), simulated annealing (SA), particle swarm optimization (PSO), artificial bee colony (ABC) algorithm, artificial immune algorithm (AIA), teaching-learning-based optimization (TLBO) algorithm and many other latest meta-heuristic techniques and their applications are discussed. This book will serve as a valuable reference for students, researchers and practitioners and help them in solving a wide range of optimization problems. .
(source: Nielsen Book Data)

• Sentiment Analysis in Turkish using Transformer-based Deep Learning Models
• Mathematical Modeling of an Antenna Device Based on a T-shaped Waveguide of the Microwave Range
• Higher-order and stable numerical scheme for nonlinear diffusion system via compact finite difference and adaptive step-size Runge-Kutta methods
• Explainable Artificial Intelligence (XAI) for Deep Learning Based Intrusion Detection Systems
• A Color Channel Based Analysis on Image Tessellation
• Modeling of Shear Strength of Basalt Fiber Reinforced Clay (BFRC) Soil Using Artificial Neural Network (ANN)
• Change of the Internet with Blockchain and Metaverse Technologies
• A Language-Free Hate Speech Identification on Code-Mixed Conversational Tweets
• Decision Trees in Causal Inference
• The Resilience of Unmanned Aerial Vehicles to Cyberattacks and Assessment of Potential Threats.

As general, this book is a collection of the most recent, quality research papers regarding applications of Artificial Intelligence and Applied Mathematics for engineering problems. The papers included in the book were accepted and presented in the 4th International Conference on Artificial Intelligence and Applied Mathematics in Engineering (ICAIAME 2022), which was held in Baku, Azerbaijan (Azerbaijan Technical University) between May 20 and 22, 2022. Objective of the book content is to inform the international audience about the cutting-edge, effective developments and improvements in different engineering fields. As a collection of the ICAIAME 2022 event, the book gives consideration for the results by especially intelligent system formations and the associated applications. The target audience of the book is international researchers, degree students, practitioners from industry, and experts from different engineering disciplines.

• Forward
• Preface
• Conference Committees
• Part I Theory and Application of Intelligent Computing
• Part II Intelligent Information System and Management Decision
• Part III Artificial Intelligence and Robots
• Part IV Mechanical design and intelligent manufacturing
• Part V Intelligent control and detection technology
• Index.

This book is a collection of selected papers submitted to the 2022 International Conference on Intelligent Systems Design and Engineering Applications organized in Tokyo, Japan, May 13-15, 2022 (ISDEA2022). The book is organized according to the conferences five major themes, including 1) Theory and Application of Intelligent Computing, 2) Intelligent Information System and Management Decision, 3) Artificial Intelligence and Robots, 4) Mechanical design and intelligent manufacturing and 5) Intelligent control and detection technology. ISDEA establishes a platform for researchers and scholars working in the field of intelligent systems design and engineering applications to present their newest research results, exchange innovative ideas, propose new models, as well as demonstrate advanced methodologies and novel design and systems.

• Part I: Foundations of Chinese AI power
• 1. State plans, research, and funding
• 2. China's AI companies: hybrid players
• 3. Foreign support, alliances, and technology transfer Part II: China and the world
• 4. China's quest for AI talent
• 5. Academic literature: quantitative and qualitative analyses
• 6. The balance sheet: China's AI advantages and challenges Part III: Impact on cutting-edge disciplines
• 7. Chinese AI and neuroscience
• 8. Chinese AI and biology
• 9. China at the Nexus of AI and Quantum Computing Part IV: AI in the shadows
• 10. AI in the Chinese military
• 11. Cyber and influence operations
• 12. AI and the surveillance statePart V: AI hazards and safety
• 13. Future paths and challenges
• 14. AI safeguards: views inside and outside China
• 15. Measuring risk and monitoring development.
• (source: Nielsen Book Data)

This book provides a comprehensive account of Chinese AI in its various facets, based on primary Chinese-language sources. China's rise as an AI power is an event of importance to the world and a potential challenge to liberal democracies. Filling a gap in the literature, this volume is fully documented, data-driven, and presented in a scholarly format suitable for citation and for supporting downstream research, while also remaining accessible to laypersons. It brings together 15 recognized international experts to present a full treatment of Chinese artificial intelligence. The volume contains chapters on state, commercial, and foreign sources of China's AI power; China's AI talent, scholarship, and global standing; the impact of AI on China's development of cutting-edge disciplines; China's use of AI in military, cyber, and surveillance applications; AI safety, threat mitigation, and the technology's likely trajectory. The book ends with recommendations drawn from the authors' interactions with policymakers and specialists worldwide, aimed at encouraging AI's healthy development in China and preparing the rest of the world to engage with it. This book will be of much interest to students of Chinese politics, science and technology studies, security studies and international relations.
(source: Nielsen Book Data)

• Intro
• Preface
• Contents
• About the Editors
• Power System Technologies
• Investigating the Application of Ethereum Smart Contracts in Energy Exchanges
• 1 Introduction
• 2 Digital Energy Ecosystem
• 3 Smart Contract Creation
• 3.1 Agreement Modelling
• 3.2 Smart Contract Definition
• 4 Smart Contract Deployment
• 5 Smart Contract Interaction
• 6 Conclusion
• References
• Feasibility Analysis of V2G Operation in India and Cost Minimization for EV Car Parks Using Firefly Algorithm
• 1 Introduction
• 2 Literature Review

• 3 Development of the Model for Feasibility Analysis of V2G Operation in India
• 3.1 Component Information
• 3.2 Simulation Model
• 3.3 Feasibility Analysis Objectives
• 4 Mathematical Model for Cost Minimization of V2G Enabled EV Charging in a Car Park
• 5 Firefly Algorithm
• 6 Optimization Implementation Procedure of the Proposed System
• 7 Results
• 7.1 Feasibility Analysis of the Proposed System Using HOMER Pro Software
• 7.2 Cost Optimization Results Using MATLAB/Simulink Software
• 8 Conclusion
• References

• Piezoelectric Sensors for the Conversion of Noise Pollution into Electricity
• 1 Introduction
• 1.1 Impact of Noise Pollution on Human Health
• 1.2 Potential of Noise Pollution
• 2 Piezoelectric Sensor for Noise Pollution Energy Converter
• 3 Role of Resonator as Pre-amplifier
• 4 Noise/Sound to Electric Energy Conversion
• 5 Practical Model of Noise Pollution Energy Converter
• 6 Conclusion
• References
• Implementation of Single-Phase Cascaded Seven-Level Inverter with Non-isolated Converter
• 1 Introduction
• 2 Cascaded H-Bridge (CHB) MLI
• 2.1 Cascaded Seven-Level Inverter

• 2.2 Projected Seven-Level Cascaded H-Bridge MLI
• 3 Modes of the Process of the Designed Technique
• 4 Results and Discussion
• 4.1 Proposed Arrangement Simulation Results
• 4.2 Proposed Arrangement PROTEUS Setup
• 5 Conclusion
• References
• An Adaptive and Efficient VSC-MTDC Controller for DC Voltage Regulation and Frequency Stability in AC Network
• 1 Introduction
• 2 Dual-Droop Control for Multi-terminal HVDC Grid
• 3 Proposed Dual-Droop Control Strategy
• 4 Simulations and Result
• 5 Conclusion
• References

• Planning of Load Frequency Control in Two Degrees of Freedom PID Controller Using MFO Technique in 2 Area Power System
• 1 Introduction
• 2 System Understudy
• 3 2-DOF and PID Controller
• 4 Moth Flow Algorithm
• 5 Simulation Result
• 6 Conclusion
• References
• Optimization of Cost and Sensitivity Analysis of a Standalone Microgrid
• 1 Introduction
• 2 Proposed Scheme
• 2.1 Determination of Daily Load Profile
• 2.2 Metrological Data
• 2.3 Schematic Model Diagram
• 2.4 Problem Description
• 3 Results and Discussion
• 3.1 Cost and Sensitivity Analysis
• 3.2 Economic Analysis

This book constitutes selected peer-reviewed proceedings of the 2nd International Conference on Signals, machines, and Automation (SIGMA 2022). This book includes papers on technologies related to electric power, manufacturing processes & automation, biomedical & healthcare, communication & networking, image processing, and computation intelligence. The book will serve as a valuable reference resource for beginners as well as advanced researchers in the areas of engineering & technology.

• Intro
• General Committees
• Honorary Chairs
• General Chair
• Conference Chairs
• Organizing Committee
• Secretary and Social Media
• Accommodation and Registration/Venue Desk
• Travel/Transportation
• Web/Design/Conference Session
• Scientific Committee
• Keynote Speaks
• ICAIAME 2021 Keynote Speakers
• Foreword
• Preface
• Contents
• About the Conference
• Scope/Topics
• Conference Scope/Topics (as not limited to)
• Conference Posters
• 1 Implementation of Basic Math Processing Skills with Neural Arithmetic Expressions in One and Two Stage Numbers
• 1.1 Introduction

• 1.1.1 Neural Arithmetic Expressions and Logic Units
• 1.1.2 Long Short-Term Memory Algorithm
• 1.2 Related Work
• 1.3 Proposed Method
• 1.4 Experimental Findings
• 1.5 Conclusions
• References
• 2 An Example Application for Early Diagnosis of Retinal Diseases Using Deep Learning Methods
• 2.1 Introduction
• 2.2 Material and Method
• 2.2.1 Material
• 2.2.2 Method
• 2.3 Research Findings
• 2.4 Discussion
• 2.5 Results
• References
• 3 Autonomous Parking with Continuous Reinforcement Learning
• 3.1 Introduction
• 3.2 Related Works
• 3.2.1 Deep Q Networks

• 3.2.2 Deep Deterministic Policy Gradient Algorithm
• 3.2.3 Twin Delayed Temporal Difference Algorithm
• 3.2.4 Soft Actor Critic Algorithm
• 3.2.5 Hindsight Experience Replay Algorithm
• 3.2.6 Parking Environment Simulation Model
• 3.3 Experiments and Results
• 3.4 Conclusions and Future Work
• References
• 4 Design and Manufacturing of a 3 DOF Robot with Additive Manufacturing Methods
• 4.1 Introduction
• 4.2 Material and Method
• 4.2.1 Material
• 4.3 Method
• 4.4 Findings and Discussion
• 4.5 Conclusion
• References

• 5 Real-Time Mask Detection Based on Artificial Intelligence Using Renewable Energy System Unmanned Aerial Vehicle
• 5.1 Introduction
• 5.2 Related Studies
• 5.3 Material and Method
• 5.3.1 Material
• 5.3.2 Material and Method
• 5.4 Research Findings
• 5.5 Conclusion
• References
• 6 Investigation of Effect of Wrapping Length on the Flexural Properties of Wooden Material in Reinforcement with Aramid FRP
• 6.1 Introduction
• 6.2 Material and Method
• 6.3 Results
• 6.4 Conclusions
• References
• 7 Deep Learning-Based Air Defense System for Unmanned Aerial Vehicles
• 7.1 Introduction

• 7.2 Material and Method
• 7.2.1 Material
• 7.2.2 Method
• 7.3 Research Findings
• 7.3.1 MobileNetV2 Training Results
• 7.3.2 Xception Training Results
• 7.3.3 InceptionV3 Training Results
• 7.4 Results
• References
• 8 Strategic Framework for ANFIS and BIM Use on Risk Management at Natural Gas Pipeline Project
• 8.1 Introductıon
• 8.2 Literature
• 8.3 Materials and Methods
• 8.3.1 Artificial Neural Networks (ANN)
• 8.3.2 Structure of Artificial Neural Network
• 8.3.3 Fuzzy Inference System
• 8.3.4 Adaptive Neuro-Fuzzy Inference System-ANFIS

This book brings together the most recent, quality research papers accepted and presented in the 3rd International Conference on Artificial Intelligence and Applied Mathematics in Engineering (ICAIAME 2021) held in Antalya, Turkey between 1-3 October 2021. Objective of the content is to provide important and innovative research for developments-improvements within different engineering fields, which are highly interested in using artificial intelligence and applied mathematics. As a collection of the outputs from the ICAIAME 2021, the book is specifically considering research outcomes including advanced use of machine learning and careful problem designs on human-centred aspects. In this context, it aims to provide recent applications for real-world improvements making life easier and more sustainable for especially humans. The book targets the researchers, degree students, and practitioners from both academia and the industry.
(source: Nielsen Book Data)

• Smart Grid and Net Metering Impact in Current Scenario of Power System.- Machine Learning Based Approach for Myocardial Infarction.- Joyful Jaccard: An Analysis of Jaccard-based Similarity Measures in Collaborative Recommendations.- An Improved Reversible Data Hiding Technique for Encrypted Images Using Difference Error Expansion.- Assessment of Image Quality Metric by the means of Various Preprocessing Filters for Lung CT Scan Images.- A New Approach for Acute Lymphocytic Leukemia Identification Using Transfer Learning.- A Hybrid Machine Learning Approach for Customer Segmentation Using RFM Analysis.- AMD-net: Automatic Medical Diagnoses using Retinal OCT Images.- Performance Interpretation of Supervised Artificial Neural Network Highlighting Role of Weight and Bias for Link Prediction.- Using Big Data Analytics on Social Media to Analyze Tourism Service Encounters.
• (source: Nielsen Book Data)

This book comprises select papers from the International Conference on Artificial Intelligence and Sustainable Engineering (AISE 2020). The volume focuses on the recent advancements in artificial intelligence and addresses how it is useful in achieving truly sustainable solutions. The key strands of this book include artificial intelligence in healthcare, IoT for modern life, security and surveillance, big data analytics, machine learning and computing, communication technologies, gesture technology, virtual intelligence, and audio & speech processing. The book addresses sustainability challenges in various computing techniques and opportunities for sustainable engineering based on AI and supporting tools such as engineering design for sustainable development using IoT/AI, smart cities: waste minimization, remanufacturing, reuse and recycling technologies using IoT/AI, industry 4.0, intelligent and smart grid systems, energy conservation using technology, green engineering/technology, robotic process automation (RPA) and water and air quality management. This book can be a valuable resource for academicians, researchers, and professionals working in AI and its applications.
(source: Nielsen Book Data)

• Chapter 1: An Overview of Blasting Operations and Possible Techniques to Solve Environmental Issues of Blasting Chapter 2: Machine Learning Techniques to Solve Problems Related to Rock Fragmentations Induced by Blasting
• Chapter 3: Applications of AI and ML to Predict Back-Break and Flyrock Distance Resulting from Blasting
• Chapter 4: Blast-Induced Air and Ground Vibrations: A Review of Soft Computing Techniques.
• (source: Nielsen Book Data)

This book gives a rigorous and up-to-date study of the various AI and machine learning algorithms for resolving environmental challenges associated with blasting. Blasting is a critical activity in any mining or civil engineering project for breaking down hard rock masses. A small amount of explosive energy is only used during blasting to fracture rock in order to achieve the appropriate fragmentation, throw, and development of muck pile. The surplus energy is transformed into unfavourable environmental effects such as back-break, flyrock, air overpressure, and ground vibration. The advancement of artificial intelligence and machine learning techniques has increased the accuracy of predicting these environmental impacts of blasting. This book discusses the effective application of these strategies in forecasting, mitigating, and regulating the aforementioned blasting environmental hazards.
(source: Nielsen Book Data)

• Application of Supervised learning for Voltage Stability Assessment.- Breast DCE-MRI Segmentation for Lesion Detection using Clustering with Fireworks Algorithm.- Swarm Programming Using Moth-Flame Optimization and Whale Optimization Algorithms.- Nonlinear Regression Analysis Using Multi-Verse Optimizer.- An Extended ACO-Based Routing Algorithm for Cognitive Radio Network.- A Review on Image Classification and Object Detection Using Deep Learning.- Kidney Lesion Segmentation in MRI Using Clustering with Salp Swarm Algorithm.- Smart Approach to Optical Character Recognition and Ubiquitous Speech Synthesis using Real-Time Deep Learning Algorithms.- Sine Cosine Algorithm with Centroid Opposition-based Computation.- Data Mining Techniques for Fraud Detection - Credit Card Frauds.
• (source: Nielsen Book Data)

This book presents best selected papers presented at the First Global Conference on Artificial Intelligence and Applications (GCAIA 2020), organized by the University of Engineering & Management, Jaipur, India, during 8-10 September 2020. The proceeding will be targeting the current research works in the domain of intelligent systems and artificial intelligence.
(source: Nielsen Book Data)

• Prediction of Polycystic Ovary Syndrome (PCOS) using Optimized Machine Learning Classifiers
• Literature Review: A Comparative Study of Software Defect Prediction Techniques
• Crop Recommendation using Machine Learning Algorithms and Soil Attributes Data
• Application of Machine Learning Models to Improve the Accuracy of Earnings Management Prediction
• Ensemble of Parametrized Quantum LSTM Neural Networks for Multimodal Stress Monitoring
• Evolutionary Algorithms for Marine Dynamical Systems: Towards Sustainable Renewable Energy Harvesting from Oshore Environment
• Comparison of Different Swarm Based Nature Inspired Algorithm for solution of Optimization Problem
• Assessment of Firms Performance by Employing Text Mining Techniques
• Decisions Prediction Techniques using Language Processing and Learning Algorithms
• Machine Learning-based Tool to Classify Online Toxic Comments.

This book gathers outstanding research papers presented in the 3rd International Conference on Artificial Intelligence: Advances and Application (ICAIAA 2022), held in Poornima College of Engineering, Jaipur, India, during April 2324, 2022. This book covers research works carried out by various students such as bachelor, master and doctoral scholars, faculty and industry persons in the area of artificial intelligence, machine learning, deep learning applications in health care, agriculture, and business, security. It also covers research in core concepts of computer networks, intelligent system design and deployment, real-time systems, WSN, sensors and sensor nodes, SDN, NFV, etc.

• Fault Analysis and Protection Scheme for DC Microgrid.- A Case Study on Electric Vehicle Conversion from an Internal Combustion Engine Vehicle.- Image Processing Using Elephant Herding Optimization: A Review.- A Review on IOT based Efficient Energy Management System for Smart homes.- Minimization of Tie-line Power Fluctuations using GCSC with Gas-Thermal -EV System for LFC Considering Time-Delay Effect.- Investigation of Timing Issues of True Single-Phase Clock Circuits for Nanodevices.- Comparative Analysis of Machine Learning Techniques for Software Effort Estimation.- A Review of Factors Affecting the Sensitivity of Piezoresistive Microcantilever based MEMS Force Sensor.- Dynamics Modeling and Motion Simulation of a Segway Robotic Transportation System.- Microgrid Energy Management Strategy for Low Dynamics Load Applications using Simulink.
• (source: Nielsen Book Data)

This book compiles the best selected research papers presented during the 2nd International Conference on Intelligent Computing Techniques for Smart Energy Systems (ICTSES 2021), held at Manipal University, Jaipur, Rajasthan, India. It presents the diligent work of the research community where intelligent computing techniques are applied in allied fields of engineering ranging from engineering materials to electrical engineering to electronics and communication engineering- to computer-related fields. The theoretical research concepts are supported with extensive reviews highlighting the trends in the possible and real-life applications of computational intelligence. The high-quality content with broad range of the topics is thoroughly peer-reviewed and published on suitable recommendations.
(source: Nielsen Book Data)

• Cover
• Title Page
• Copyright Page
• Contents
• Preface
• Chapter 1 IoT-Based Battery Management System for Hybrid Electric Vehicle
• 1.1 Introduction
• 1.2 Battery Configurations
• 1.3 Types of Batteries for HEV and EV
• 1.4 Functional Blocks of BMS
• 1.4.1 Components of BMS System
• 1.5 IoT-Based Battery Monitoring System
• References
• Chapter 2 A Noble Control Approach for Brushless Direct Current Motor Drive Using Artificial Intelligence for Optimum Operation of the E
• 2.1 Introduction
• 2.2 Introduction of Electric Vehicle

• 2.2.1 Historical Background of Electric Vehicle
• 2.2.2 Advantages of Electric Vehicle
• 2.2.2.1 Environmental
• 2.2.2.2 Mechanical
• 2.2.2.3 Energy Efficiency
• 2.2.2.4 Cost of Charging Electric Vehicles
• 2.2.2.5 The Grid Stabilization
• 2.2.2.6 Range
• 2.2.2.7 Heating of EVs
• 2.2.3 Artificial Intelligence
• 2.2.4 Basics of Artificial Intelligence
• 2.2.5 Advantages of Artificial Intelligence in Electric Vehicle
• 2.3 Brushless DC Motor
• 2.4 Mathematical Representation Brushless DC Motor
• 2.5 Closed-Loop Model of BLDC Motor Drive
• 2.5.1 P-I Controller & I-P Controller

• 2.6 PID Controller
• 2.7 Fuzzy Control
• 2.8 Auto-Tuning Type Fuzzy PID Controller
• 2.9 Genetic Algorithm
• 2.10 Artificial Neural Network-Based Controller
• 2.11 BLDC Motor Speed Controller With ANN-Based PID Controller
• 2.11.1 PID Controller-Based on Neuro Action
• 2.11.2 ANN-Based on PID Controller
• 2.12 Analysis of Different Speed Controllers
• 2.13 Conclusion
• References
• Chapter 3 Optimization Techniques Used in Active Magnetic Bearing System for Electric Vehicles
• 3.1 Introduction
• 3.2 Basic Components of an Active Magnetic Bearing (AMB)
• 3.2.1 Electromagnet Actuator

• 3.2.2 Rotor
• 3.2.3 Controller
• 3.2.3.1 Position Controller
• 3.2.3.2 Current Controller
• 3.2.4 Sensors
• 3.2.4.1 Position Sensor
• 3.2.4.2 Current Sensor
• 3.2.5 Power Amplifier
• 3.3 Active Magnetic Bearing in Electric Vehicles System
• 3.4 Control Strategies of Active Magnetic Bearing for Electric Vehicles System
• 3.4.1 Fuzzy Logic Controller (FLC)
• 3.4.1.1 Designing of Fuzzy Logic Controller (FLC) Using MATLAB
• 3.4.2 Artificial Neural Network (ANN)
• 3.4.2.1 Artificial Neural Network Using MATLAB
• 3.4.3 Particle Swarm Optimization (PSO)

• 3.4.4 Particle Swarm Optimization (PSO) Algorithm
• 3.4.4.1 Implementation of Particle Swarm Optimization for Electric Vehicles System
• 3.5 Conclusion
• References
• Chapter 4 Small-Signal Modelling Analysis of Three-Phase Power Converters for EV Applications
• 4.1 Introduction
• 4.2 Overall System Modelling
• 4.2.1 PMSM Dynamic Model
• 4.2.2 VSI-Fed SPMSM Mathematical Model
• 4.3 Mathematical Analysis and Derivation of the Small-Signal Model
• 4.3.1 The Small-Signal Model of the System
• 4.3.2 Small-Signal Model Transfer Functions
• 4.3.3 Bode Diagram Verification
• 4.4 Conclusion

Electric vehicles are changing transportation dramatically and this unique book merges the many disciplines that contribute research to make EV possible, so the reader is informed about all the underlying science and technologies driving the change. An emission-free mobility system is the only way to save the world from the greenhouse effect and other ecological issues. This belief has led to a tremendous growth in the demand for electric vehicles (EV) and hybrid electric vehicles (HEV), which are predicted to have a promising future based on the goals fixed by the European Commission's Horizon 2020 program. This book brings together the research that has been carried out in the EV/HEV sector and the leading role of advanced optimization techniques with artificial intelligence (AI). This is achieved by compiling the findings of various studies in the electrical, electronics, computer, and mechanical domains for the EV/HEV system. In addition to acting as a hub for information on these research findings, the book also addresses the challenges in the EV/HEV sector and provides proven solutions that involve the most promising AI techniques. Since the commercialization of EVs/HEVs still remains a challenge in industries in terms of performance and cost, these are the two tradeoffs which need to be researched in order to arrive at an optimal solution. Therefore, this book focuses on the convergence of various technologies involved in EVs/HEVs. Since all countries will gradually shift from conventional internal combustion (IC) engine-based vehicles to EVs/HEVs in the near future, it also serves as a useful reliable resource for multidisciplinary researchers and industry teams.
(source: Nielsen Book Data)

• pt. 1. Frameworks
• pt. 2. Algorithm integration
• pt. 3. Applications.

We often come across computational optimization virtually in all branches of engineering and industry.¡Many engineering problems involve heuristic search and optimization, and, once discretized, may become combinatorial in nature, which gives rise to certain difficulties in terms of solution procedure. Some of these problems have enormous search spaces, are NP-hard and hence require heuristic solution techniques. Another difficulty is the lack of ability of classical solution techniques to determine appropriate optima of non-convex problems. Under these conditions, recent advances in computational optimization techniques have been shown to be advantageous and successful compared to classical approaches. ¡ This Volume presents some of the latest developments with a focus on the design of algorithms for computational optimization and their applications in practice.¡Through the chapters of this book, researchers and practitioners share their experience and newest methodologies with regard to intelligent optimization and provide various case studies of the application of intelligent optimization techniques in real-world applications. This book can serve as an excellent reference for researchers and graduate students in computer science, various engineering disciplines and the industry.

• Introduction and Overview: Hybrid Metaheuristics in Structural Engineering - Including Machine Learning Applications
• The Development of Hybrid Metaheuristics in Structural Engineering
• Optimum Design of Reinforced Concrete Columns in Case of Fire
• Hybrid Social Network Search and Material Generation Algorithm for Shape and Size Optimization of Truss Structures
• Development of a Hybrid Algorithm for Optimum Design of a Large-Scale Truss Structure

From the start of life, people used their brains to make something better in design in ordinary works. Due to that, metaheuristics are essential to living things, and several inspirations from life have been used in the generation of new algorithms. These algorithms have unique features, but the usage of different features of different algorithms may give more effective optimum results in means of precision in optimum results, computational effort, and convergence. This book is a timely book to summarize the latest developments in the optimization of structural engineering systems covering all classical approaches and new trends including hybrids metaheuristic algorithms. Also, artificial intelligence and machine learning methods are included to predict optimum results by skipping long optimization processes. The main objective of this book is to introduce the fundamentals and current development of methods and their applications in structural engineering.

• What is Intelligent Construction?.- Representing things in systematic Approach.- Make Machines Capable of Learning.- Entering a Data Era.- Understanding Perception Technology.- The Intelligence of Engineering Construction.- The Road to the Future.
• (source: Nielsen Book Data)

This book expounds on the related technologies of intelligent transportation infrastructure construction. Based on the essential characteristics of intelligent construction, "perception, analysis, decision-making, and execution, " the basic structure of intelligent construction technology (ICT) is established. With the integration of engineering construction technologies, the analyses of the essence of intelligent algorithms and the feasibility of Artificial Intelligence (AI) are provided. The book introduces the essential characteristics of Big Data and the Internet of Things and their relationship with engineering construction. On this basis, the feasibility and implementation plan of intelligent technology applications in design, construction, and maintenance are analyzed and demonstrated with engineering examples. The book also combines ICT with intelligent construction talent training, the professional knowledge required for intelligent construction, and the theoretical basis to provide the methods for mastering new technologies. This book can be used by technical personnel in related fields such as highways, railways, airports, and urban road construction to understand and master innovative, intelligent construction technologies. It can also be a reference book for ICT-related college courses.
(source: Nielsen Book Data)

• Part I. Hybrid Energetic Systems PV-WIND, with Energy Storage
• Part II. Heuristic Optimization, Modeling and Control of Energetic Systems
• Part III. Engineering Applications of Artificial Intelligence
• Part IV. Internet of Things, Database and Transmission
• Part V. Power and Materials in Renewable Energetic Systems. 96 papers.

This proceedings book emphasizes adopting artificial intelligence-based and sustainable energy efficiency integrated with clear objectives, to involve researchers, students, and specialists in their development and implementation adequately in achieving objectives. The integration of artificial intelligence into renewable energetic systems would allow the rapid development of a knowledge-based economy suitable to the energy transition, while fully integrating the renewables into the global economy. This is how artificial intelligence has hand in by conceptualizing this transition and above all by saving time. The knowledge economy is valuated within the smart cities, which are fast becoming the favorite places where the energy transition will take place efficiently and intelligently by implementing integrated approaches to energy saving and energy supply and integrated urban approaches that go beyond individual interventions in buildings or transport modes using information and communication technologies.
(source: Nielsen Book Data)

These proceedings address the latest developments in the broad area of intelligent construction integrated in the mission of the International Society for Intelligent Construction (ISIC) which aims to promote intelligent construction technologies applications from the survey, design, construction, operation, and maintenance/rehabilitation by adapting to changes of environments and minimizing risks. Its goals are to improve the quality of construction, cost-saving, and safety, exploring fundamental issues related to the application and use of Artificial Intelligence (AI) and Machine Learning techniques and technology. ISIC 2022 is the 3rd ISIC international conference, held in Guimaraes, Portugal on September 6-9, 2022, and follows the previous successful instalments of the conference series in China (2019) and USA (2017). It took a holistic approach to integrate civil engineering, construction machinery, electronic sensor technology, survey/testing technologies, information technology/computing, and other related fields in the broad area of intelligent construction. The respective contributions cover the following topics: Artificial Intelligence for Design and the Built Environment, Building Information Modelling (BIM) and Construction Automation and Robotics, Intelligent Construction, Sustainable Construction, and Sustainable and Smart Infrastructures. Given its broad range of coverage, the book will benefit students, educators, researchers and professionals practitioners alike, encouraging these readers to help the intelligent construction community into the digital era and with a vision on societal issues.
(source: Nielsen Book Data)

• Chapter 1. Process parameters optimization by Taguchi method and Whale optimization algorithm of Lathe turning on EN24 steel for prediction of surface roughness
• Chapter 2. Optimization of TWR and SR of superalloy Al/9.6B4C in EDM using advanced optimization techniques
• Chapter 3. Simulation and comparative analysis of sardar sarovar reservoir by meta-heuristic algorithm
• Chapter 4. Determination of Thickness and Refractive Index of Antireflection Coating Thin-Films from Reflectivity Spectrum using Jaya Optimization Algorithm
• Chapter 5. Optimization of worm gear drive for improving efficiency using RCGA
• Chapter 6. Comparing a Parameter Less Technique Jaya with Parameters Based Evolutionary Algorithms
• Chapter 7. Optimal Sizing of PV/Wind/Battery stand-alone hybrid renewable energy system using TLBO algorithm
• Chapter 8. MOJAYA optimization of machining parameters coupled with R-method for the generation of micro holes on GFRP composite using an in-house developed -ECDM system
• Chapter 9. Enhanced Fruit Fly Optimization Algorithm for Node Capture Attack in WSN
• Chapter 10. Optimization of Construction Scheduling with Rao Algorithm
• Chapter 11. Using Meta-Heuristic Optimization Methods in Solving Time-Cost-Quality Trade-off Problems
• Chapter 12. A Particle Swarm Optimization based model for Quality, Safety trade-off optimization under constraint duration and cost of construction project
• Chapter 13. Optimum design of pipe network using Rao algorithm
• Chapter 14. Multi-Objective Thermal Exchange Optimization for Truss structure
• Chapter 15. Shape optimization of structures considering varying geometrical and material parameters.

This book comprises peer-reviewed papers presented at the International Conference on Advanced Engineering Optimization Through Intelligent Techniques (AEOTIT) 2022. The book combines contributions from academics and industry professionals and covers advanced optimization techniques across all major engineering disciplines like mechanical, manufacturing, civil, automobile, electrical, chemical, computer, and electronics engineering. The book discusses different optimization techniques and algorithms such as genetic algorithm, non-dominated sorting genetic algorithm-II, and III, differential search, particle swarm optimization, fruit fly algorithm, cuckoo search, teachinglearning-based optimization algorithm, grey wolf optimization, Jaya algorithm, Rao algorithms, and many other latest meta-heuristic techniques and their applications. Various multi-attribute decision-making methods such as AHP, TOPSIS, ELECTRE, PROMETHEE, DEMATEL, R-method, fuzzy logic, and their applications are also discussed. This book serves as a valuable reference for students, researchers, and practitioners and helps them in solving a wide range of optimization problems.

• 1. Methods and algorithms for fuzzy cognitive map-based modeling / Elpiniki I. Papageorgiou and Jose L. Salmeron
• 2. Fuzzy cognitive maps as representations of mental models and group beliefs / S.A. Gray, E. Zanre and S.R.J. Gray
• 3. FCM relationship modeling for engineering systems / O. Motlagh, S.H. Tang, F.A. Jafar and W. Khaksar
• 4. Using RuleML for representing and prolog for simulating fuzzy cognitive maps / Athanasios Tsadiras and Nick Bassiliades
• 5. Fuzzy web knowledge aggregation, representation, and reasoning for online privacy and reputation management / Edy Portmann and Witold Pedrycz
• 6. Decision making by rule-based fuzzy cognitive maps : an approach to implement student-centered education / A. Pena-Ayala and J.H. Sossa-Azuela
• 7. Extended evolutionary learning of fuzzy cognitive maps for the prediction of multivariate time-series / Wojciech Froelich and Elpiniki I. Papageorgiou
• 8. Synthesis and analysis of multi-step learning algorithms for fuzzy cognitive maps / Alexander Yastrebov and Katarzyna Piotrowska
• 9. Designing and training relational fuzzy cognitive maps / Grzegorz Slon and Alexander Yastrebov
• 10. Cooperative autonomous agents based on dynamical fuzzy cognitive maps / Marcio Mendonca, Lucia Valeria Ramos de Arruda and Flavio Neves-Jr.
• 11. FCM-GUI : a graphical user interface for big bang-big crunch learning of FCM / Engin Yesil, Leon Urbas and Anday Demirsoy
• 12. JFCM : a Java library for fuzzy cognitive maps / Dimitri De Franciscis
• 13. Use and evaluation of FCM as a tool for long term socio ecological research / Martin Wildenberg, Michael Bachhofer, Kirsten G.Q. Isak and Flemming Skov
• 14. Using fuzzy grey cognitive maps for industrial processes control / Jose L. Salmeron and Elpiniki I. Papageorgiou
• 15. Use and perspectives of fuzzy cognitive maps in robotics / Jan Vascak and Napoleon H. Reyes
• 16. Fuzzy cognitive maps for structural damage detection / Ranjan Ganguli.
• 17. Fuzzy cognitive strategic maps / M. Glykas
• 18. The complex nature of migration at a conceptual level : an overlook of the internal migration experience of gebze through fuzzy cognitive mapping method / Tolga Tezcan
• 19. Understanding public participation and perceptions of stakeholders for a better management in Danube Delta Biosphere Reserve (Romania) / M.N. Vaidianu, M.C. Adamescu, M. Wildenberg and C. Tetelea
• 20. Employing fuzzy cognitive map for periodontal disease assessment / Vijay Kumar Mago, Elpiniki I. Papageorgiou and Anjali Mago.

Fuzzy Cognitive Maps (FCM) constitute cognitive models in the form of fuzzy directed graphs consisting of two basic elements: the nodes, which basically correspond to "concepts " bearing different states of activation depending on the knowledge they represent, and the "edges " denoting the causal effects that each source node exercises on the receiving concept expressed through weights. Weights take values in the interval [-1,1], which denotes the positive, negative or neutral causal relationship between two concepts. An FCM can be typically obtained through linguistic terms, inherent to fuzzy systems, but with a structure similar to the neural networks, which facilitates data processing, and has capabilities for training and adaptation. During the last 10 years, an exponential growth of published papers in FCMs was followed showing great impact potential. Different FCM structures and learning schemes have been developed, while numerous studies report their use in many contexts with highly successful modeling results. The aim of this book is to fill the existing gap in the literature concerning fundamentals, models, extensions and learning algorithms for FCMs in knowledge engineering. It comprehensively covers the state-of-the-art FCM modeling and learning methods, with algorithms, codes and software tools, and provides a set of applications that demonstrate their various usages in applied sciences and engineering. -- Provided by publisher