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• Accent Classification of the Three Major Nigerian Indigenous Languages Using 1D CNN LSTM Network Model.- Automatic Glaucoma Diagnosis in Digital Fundus images using Deep CNNs.- Deep Learning based Diabetic Retinopathy Prediction of Colored Fundus Images with Parameter Tuning.- Fractal Analysis of Heart Dynamics during Attention Task.- Assessment of Health Care Techniques in IoT.- English Numerals Recognition System using Novel Curve Coding.- Clustering and Employability Profiling of Engineering Students.- Universal Approach for Detection of Spot Diseases in Plants.- Stereo Camera and LIDAR Sensor Fusion based Collision Warning System for Autonomous Vehicles.
• (source: Nielsen Book Data)

This book highlights recent advances in computational intelligence for signal processing, computing, imaging, artificial intelligence, and their applications. It offers support for researchers involved in designing decision support systems to promote the societal acceptance of ambient intelligence, and presents the latest research on diverse topics in intelligence technologies with the goal of advancing knowledge and applications in this rapidly evolving field. As such, it offers a valuable resource for researchers, developers and educators whose work involves recent advances and emerging technologies in computational intelligence.
(source: Nielsen Book Data)

• Smart Inventory Management using Electronic Sensor Based Computational Intelligence.- Computational Intelligence for Data Analytics.- Review on Current Trends of Deep Learning.- A Variant of Secret Sharing Protected with Poly-1305.- Enhancing Gadgets for Blinds through Scale Invariant Feature Transform.- A Study to Renovate Image Data using Data Analytics Methodologies.- Video Streaming Communication Over Vanet.- Autonomous Agents - Beginnings, Innings and Where We are Headed.
• (source: Nielsen Book Data)

This book comprehensively addresses computational intelligence, including the theories, methodologies and techniques underlying this evolving field, as well as its potential uses in various domains across the entire spectrum of the sciences (the natural sciences, health sciences, engineering, social sciences, and humanities) and in various types of business. Computational intelligence is rapidly spreading into all kinds of products and services. This calls for the adaptation of existing theories, methodologies and techniques - and the development of wholly new ones - to ensure the successful implementation of new intelligent products and services in various domains related to public organizations, businesses and everyday life. This book gathers contributions from various experts working on different aspects and implementations of computational intelligence, which address new developments in theory, analytical and numerical simulation and modeling, experimentation, deployment and case studies, results of laboratory or field operational tests, and ongoing advances in computational intelligence. It is intended for a broad audience, including researchers, engineers, policymakers, industry experts, and students, offering these readers essential information on and new inspirations regarding the potential of computational intelligence.
(source: Nielsen Book Data)

These transactions publish research in computer-based methods of computational collective intelligence (CCI) and their applications in a wide range of fields such as the semantic web, social networks, and multi-agent systems. TCCI strives to cover new methodological, theoretical and practical aspects of CCI understood as the form of intelligence that emerges from the collaboration and competition of many individuals (artificial and/or natural). The application of multiple computational intelligence technologies, such as fuzzy systems, evolutionary computation, neural systems, consensus theory, etc., aims to support human and other collective intelligence and to create new forms of CCI in natural and/or artificial systems. This thirty-second issue presents 5 selected papers in the field of management, economics and computer science.

• Performance Optimization in IoT-based Next-Generation Wireless Sensor Networks.- Enabling custom security controls as plugins in service oriented environments.- A Flexible Synchronization Protocol to Learn Hidden Topics in P2PPS Systems.- QoS Preservation in Web Service Selection.- File Assignment Control for a Web System of Contents Categorization.- Byzantine Collision-Fast Consensus Protocols.- A methodological approach for time series analysis and forecasting of web dynamics.- Static and Dynamic Group Migration Algorithms of Virtual Machines to Reduce Energy Consumption of a Server Cluster.- Unsupervised Deep Learning for Software Defined Networks Anomalies Detection.
• (source: Nielsen Book Data)

These transactions publish research in computer-based methods of computational collective intelligence (CCI) and their applications in a wide range of fields such as performance optimization in IoT, big data, reliability, privacy, security, service selection, QoS and machine learning. This thirty-third issue contains 9 selected papers which present new findings and innovative methodologies as well as discuss issues and challenges in the field of collective intelligence from big data and networking paradigms while addressing security, privacy, reliability and optimality to achieve QoS to the benefit of final users. .
(source: Nielsen Book Data)

• A probabilistic model for detecting gerrymandering in partially-contested multiparty elections / Dariusz Stolicki, Wojciech Słomczyński, and Jarosław Flis
• Power in networks : a PGI analysis of Krackhardt's kite network / Manfred J. Holler and Florian Rupp
• Orders of criticality in graph connection games / Marco Dall'Aglio, Vito Fragnelli, and Stefano Moretti
• The capacity of companies to create an early warning system for unexpected events : an explorative study / Johannes (Joost) Platje
• Electoral reform and social choice theory : piecemeal engineering and selective memory / Hannu Nurmi
• Repeated trust game : statistical results concerning time of reaction / Anna Motylska-Kuźma, Jacek Mercik, and Aleksander Buczek
• Labeled network allocation problems : an application to transport systems / Encarnación Algaba, Vito Fragnelli, Natividad Llorca, and Joaquin Sánchez-Soriano
• Seat apportionment by population and contribution in European Parliament after Brexit / Cesarino Bertini, Gianfranco Gambarelli, Izabella Stach, and Giuliana Zibetti
• The use of group decision-making to improve the monitoring of air quality / Cezary Orłowski, Piotr Cofta, Mariusz Wąsik, Piotr Welfler, and Józef Pastuszka
• Bi-proportional apportionments / Mirko Bezzi, Gianfranco Gambarelli, and Giuliana Angela Zibetti
• A probabilistic unified approach for power indices in simple games / Josep Freixas and Montserrat Pons
• The story of the poor public good index / Manfred J. Holler.

These transactions publish research in computer-based methods of computational collective intelligence (CCI) and their applications in a wide range of fields such as performance optimization in IoT, big data, reliability, privacy, security, service selection, QoS and machine learning. This thirty-fourth issue contains 12 selected papers which present new findings and innovative methodologies as well as discuss issues and challenges in the field of collective intelligence in group decision making with special emphasize given to voting theory, power indices and graphs while addressing elections, social choices, IoT and allocation algorithms.

• Machine Learning in Hybrid Environment for Information Identification with Remotely Sensed Image Data
• Clustering-Based Aggregation of High-Utility Patterns from Unknown Multi-Database
• A Study of Three Different Approaches to Point Placement on a Line in an Inexact Model
• Cinolib: A Generic Programming Header Only C++ Library for Processing Polygonal and Polyhedral Meshes
• Trust Computation in VANET Cloud
• Received Power Exploration of Cooperative WSN Deployed in Adjustable Antenna Height Environment
• A Built-in Circuit for Self-Reconfiguring Mesh-Connected Processor Arrays with Spares on Diagonal.

The LNCS journal Transactions on Computational Science reflects recent developments in the field of Computational Science, conceiving the field not as a mere ancillary science but rather as an innovative approach supporting many other scientific disciplines. The journal focuses on original high-quality research in the realm of computational science in parallel and distributed environments, encompassing the facilitating theoretical foundations and the applications of large-scale computations and massive data processing. It addresses researchers and practitioners in areas ranging from aerospace to biochemistry, from electronics to geosciences, from mathematics to software architecture, presenting verifiable computational methods, findings, and solutions, and enabling industrial users to apply techniques of leading-edge, large-scale, high performance computational methods. This, the 34th issue of the Transactions on Computational Science, contains seven in-depth papers focusing on research on data analytics using machine learning and pattern recognition, with applications in wireless networks, databases, and remotely sensed data.

• Chapter 1. Application of the Flower Pollination Algorithm in the Analysis of Micro-CT Scans (Piotr Kowalski).-
• Chapter 2. Enhancing the analysis of video time series by means of a multi-agent architecture (Luis Rodriguez-Benitez).-
• Chapter 3. On the Antecedent Sets for Fuzzy Classification of Colorectal Polyps with Stabilized KH Interpolation (Szilvia Nagy).-
• Chapter 4. How to predict consistently? (Evgenii Vityaev).-
• Chapter 5. Symbolic Unfolding of Multi-adjoint Logic Programs (Gines Moreno).-
• Chapter 6. Towards the use of hypergraphs in fuzzy logic programming (Juan Carlos Diaz-Moreno).-
• Chapter 7. Banking Applications of FCM Models (Miklos Hatwagner).-
• Chapter 8. On experimental efficiency for retraction operator to stem basis (Gonzalo A. Aranda-Corral).-
• Chapter 9. Inference of mixed information in Formal Concept Analysis (Angel Mora Bonilla).-
• Chapter 10. Unifying reducts in formal concept analysis and rough set theory (Maria Jose Benitez-Caballero).-
• Chapter 11. Similarity measure between linguistic terms by using restricted equivalence functions and its application to expert systems (Clemente Rubio Manzano).-
• Chapter 12. A New Convex Hull, Sliding Window Based Online Adaptation Method for Fixed-Structure Radial Basis Function Neural Networks (Hamid Khosravani).-
• Chapter 13. A population based metaheuristic for the Minimum Latency Problem (Boldizsar Tuu-Szabo).-
• Chapter 14. Multi-objective Fuzzy Geometric Programming Problem Using Fuzzy Geometry (Dr. Debjani Chakraborty).-
• Chapter 15. Recommendation solution in a Locate-Based Social Network via Formal Concept Analysis (Jesus Medina).-
• Chapter 16. Generalized Boolean Algebras and Applications (Andreja Tepavcevic).-
• Chapter 17. Bipolar max-product fuzzy relation equations with the product negation (M.Eugenia Cornejo).-
• Chapter 18. Direct and indirect methods for solving two-mode systems of fuzzy relation equations and inequalities (Miroslav Ciric).-
• Chapter 19. An adjoint pair for intuitionistic L-fuzzy values (Ondrej Kridlo).-
• Chapter 20. On Possibilistic Version of Distance Covariance and Correlation (Istvan Harmati).-
• Chapter 21. A Fuzzy Approach for Measuring Sentence Checkability - Preliminary Results (Hugo Farinha).-
• Chapter 22. Reduced Model Investigations supported by Fuzzy Cognitive Map to Foster Circular Economy (Adrienn Buruzs).
• (source: Nielsen Book Data)

This book presents appealing contributions on computational intelligence and mathematics, connecting both areas and offering solutions to a number of interesting, real-world problems. Such problems often require novel solutions, as complexity exceeds the tractable size. At the same time, the need for good-quality realistic solutions results in models and algorithms with a good balance of resource intensiveness and model quality (accuracy). Many areas of knowledge call for hybrid solutions that combine traditional mathematical techniques and computational intelligence based on subsymbolic knowledge representation. Important research topics are focused on developing the interaction between computational intelligence and mathematics, in order to address various challenges of the current technological age. Written by influential, leading researchers, this book discusses the latest trends in hybridising mathematics and computational intelligence.
(source: Nielsen Book Data)

• An equivalent formulation for the Shapley value.- Reflections on two old Condorcet extensions.- Transforming Games with Affinities from Characteristic into Normal Form.- Comparing Game-Theoretic and Maximum Likelihood Approaches for Network Partitioning.- Comparing results of voting by statistical rank tests.- Remarks on Unrounded Degressively Proportional Allocation.- On the Measurement of Control in Corporate Structures.- The Effect of Brexit on the Balance of Power in the European Union Council revisited: a fuzzy multicriteria attempt.- Robustness of the Government and the Parliament, and Legislative Procedures in Europe.- Should the financial decisions be made as group decisions?.- Diffusion of electric vehicles: an agent-based modelling approach.- Decision progress based on IoT for suitable smart cities.
• .
• (source: Nielsen Book Data)

These transactions publish research in computer-based methods of computational collective intelligence (CCI) and their applications in a wide range of fields such as the semantic web, social networks, and multi-agent systems. TCCI strives to cover new methodological, theoretical and practical aspects of CCI understood as the form of intelligence that emerges from the collaboration and competition of many individuals (artificial and/or natural). The application of multiple computational intelligence technologies, such as fuzzy systems, evolutionary computation, neural systems, consensus theory, etc., aims to support human and other collective intelligence and to create new forms of CCI in natural and/or artificial systems. This thirty-first issue presents 12 selected papers from the 3rd Seminar on Quantitative Methods of Group Decision Making which was held in November 2017 at the WSB University in Wroclaw.
(source: Nielsen Book Data)

• 1. Introduction
• 2. Unit commitment and economic load dispatch problem
• 3. Harmonic reduction in power systems
• 4. Voltage and frequency control in power systems
• 5. Job shop scheduling problem
• 6. Multidepot vehicle routing problem
• 7. Digital image watermarking

• Color Plates XV Preface XXXI List of Contributors XXXIII 1 Model Selection for Neural Network Models: A Statistical Perspective 1 Michele La Rocca and Cira Perna 1.1 Introduction 1 1.2 Feedforward Neural NetworkModels 2 1.3 Model Selection 4 1.3.1 Feature Selection by Relevance Measures 6 1.3.2 Some Numerical Examples 10 1.3.3 Application to Real Data 12 1.4 The Selection of the Hidden Layer Size 14 1.4.1 A Reality Check Approach 15 1.4.2 Numerical Examples by Using the Reality Check 16 1.4.3 Testing Superior Predictive Ability for Neural Network Modeling 19 1.4.4 Some Numerical Results Using Test of Superior Predictive Ability 21 1.4.5 An Application to Real Data 23 1.5 Concluding Remarks 26 References 26 2 Measuring Structural Correlations in Graphs 29 Ziyu Guan and Xifeng Yan 2.1 Introduction 29 2.1.1 Solutions for Measuring Structural Correlations 31 2.2 RelatedWork 32 2.3 Self Structural Correlation 34 2.3.1 Problem Formulation 34 2.3.2 The Measure 34 2.3.3 Computing Decayed Hitting Time 37 2.3.4 Assessing SSC 41 2.3.5 Empirical Studies 45 2.3.6 Discussions 51 2.4 Two-Event Structural Correlation 52 2.4.1 Preliminaries and Problem Formulation 52 2.4.2 Measuring TESC 53 2.4.3 Reference Node Sampling 56 2.4.4 Experiments 62 2.4.5 Discussions 70 2.5 Conclusions 72 Acknowledgments 72 References 72 3 Spectral Graph Theory and Structural Analysis of Complex Networks: An Introduction 75 Salissou Moutari and Ashraf Ahmed 3.1 Introduction 75 3.2 Graph Theory: Some Basic Concepts 76 3.2.1 Connectivity in Graphs 77 3.2.2 Subgraphs and Special Graphs 80 3.3 MatrixTheory: Some Basic Concepts 81 3.3.1 Trace and Determinant of a Matrix 81 3.3.2 Eigenvalues and Eigenvectors of a Matrix 82 3.4 Graph Matrices 83 3.4.1 Adjacency Matrix 84 3.4.2 Incidence Matrix 84 3.4.3 Degree Matrix and Diffusion Matrix 85 3.4.4 Laplace Matrix 85 3.4.5 Cut-Set Matrix 86 3.4.6 Path Matrix 86 3.5 Spectral Graph Theory: Some Basic Results 86 3.5.1 Spectral Characterization of Graph Connectivity 87 3.5.2 Spectral Characteristics of some Special Graphs and Subgraphs 89 3.5.3 SpectralTheory and Graph Colouring 91 3.5.4 SpectralTheory and Graph Drawing 91 3.6 Computational Challenges for Spectral Graph Analysis 91 3.6.1 Krylov Subspace Methods 91 3.6.2 Constrained Optimization Approach 94 3.7 Conclusion 94 References 95 4 Contagion in Interbank Networks 97 Grzegorz Ha^3aj and Christoffer Kok 4.1 Introduction 97 4.2 Research Context 99 4.3 Models 103 4.3.1 Simulated Networks 104 4.3.2 Systemic Probability Index 109 4.3.3 Endogenous Networks 110 4.4 Results 119 4.4.1 Data 119 4.4.2 Simulated Networks 120 4.4.3 Structure of Endogenous Interbank Networks 123 4.5 Stress Testing Applications 127 4.6 Conclusions 130 References 131 5 Detection, Localization, and Tracking of a Single and Multiple Targets with Wireless Sensor Networks 137 Natallia Katenka 5.1 Introduction and Overview 137 5.2 Data Collection and Fusion by WSN 138 5.3 Target Detection 141 5.3.1 Target Detection from Value Fusion (Energies) 142 5.3.2 Target Detection from Ordinary Decision Fusion 143 5.3.3 Target Detection from Local Vote Decision Fusion 144 5.4 Single Target Localization and Diagnostic 149 5.4.1 Localization and Diagnostic from Value Fusion (Energies) 150 5.4.2 Localization and Diagnostic from Ordinary Decision Fusion 151 5.4.3 Localization and Diagnostic from Local Vote Decision Fusion 152 5.4.4 Hybrid Maximum Likelihood Estimates 153 5.4.5 Properties of Maximum-Likelihood Estimates 154 5.5 Multiple Target Localization and Diagnostic 157 5.5.1 Multiple Target Localization from Energies 158 5.5.2 Multiple Target Localization from Binary Decisions 158 5.5.3 Multiple Target Localization from Corrected Decisions 159 5.6 Multiple Target Tracking 161 5.7 Applications and Case Studies 165 5.7.1 The NEST Project 166 5.7.2 The ZebraNet Project 168 5.8 Final Remarks 170 References 171 6 Computing in Dynamic Networks 173 Othon Michail, Ioannis Chatzigiannakis, and Paul G. Spirakis 6.1 Introduction 173 6.1.1 Motivation-State of the Art 173 6.1.2 Structure of the
• Chapter 177 6.2 Preliminaries 177 6.2.1 The Dynamic Network Model 177 6.2.2 Problem Definitions 179 6.3 Spread of Influence in Dynamic Graphs (Causal Influence) 180 6.4 Naming and Counting in Anonymous Unknown Dynamic Networks 182 6.4.1 Further RelatedWork 183 6.4.2 Static Networks with Broadcast 183 6.4.3 Dynamic Networks with Broadcast 186 6.4.4 Dynamic Networks with One-to-Each 188 6.4.5 Higher Dynamicity 195 6.5 Causality, Influence, and Computation in Possibly Disconnected Synchronous Dynamic Networks 196 6.5.1 Our Metrics 196 6.5.2 Fast Propagation of Information under Continuous Disconnectivity 201 6.5.3 Termination and Computation 203 6.6 Local CommunicationWindows 212 6.7 Conclusions 215 References 216 7 Visualization and Interactive Analysis for Complex Networks by means of Lossless Network Compression 219 Matthias Reimann, Loic Royer, Simone Daminelli, and Michael Schroeder 7.1 Introduction 219 7.1.1 Illustrative Example 221 7.2 Power Graph Algorithm 221 7.2.1 Formal Definition of Power Graphs 221 7.2.2 Semantics of Power Graphs 222 7.2.3 Power Graph Conditions 222 7.2.4 Edge Reduction and Relative Edge Reduction 223 7.2.5 Power Graph Extraction 225 7.3 Validation Edge Reduction Differs from Random 227 7.4 Graph Comparison with Power Graphs 228 7.5 Excursus: Layout of Power Graphs 229 7.6 Interactive Visual Analytics 231 7.6.1 Power Edge Filtering 232 7.7 Conclusion 234 References 234 Index 237.
• (source: Nielsen Book Data)

This comprehensive introduction to computational network theory as a branch of network theory builds on the understanding that such networks are a tool to derive or verify hypotheses by applying computational techniques to large scale network data. The highly experienced team of editors and high-profile authors from around the world present and explain a number of methods that are representative of computational network theory, derived from graph theory, as well as computational and statistical techniques. With its coherent structure and homogenous style, this reference is equally suitable for courses on computational networks.
(source: Nielsen Book Data)

• Neural Network and Applications: Pattern Recognition via Perceptrons (W K Ling)
• Artificial Neural Network Modeling with Application to Nonlinear Dynamics (Y Zhao)
• Solving Matrix Eigen Problems by Neural Networks (Y Liu and Z You)
• Support Vector Machines and Applications: Cardio Respriatory Response Estimation by using Non-invasive Sensors (S Su et al.)
• Maximal Margin Algorithms for Pose Estimation (Y Guo et al.)
• Handwritten Recognition using SVM (H K Lam et al.)
• Fuzzy Logic and Applications: Detection of Nocturnal Hypoglycemic Episodes with Type1 Diabetes using Particle Swarm Optimization-based Fuzzy Inference System (S H Ling & H Nguyen)
• Fuzzy Controllers for Nonlinear Systems (H K Lam)
• Automated Screw Insertion Monitoring using Neural Networks: A Computational Intelligence Approach to Assembly in Manufacturing (K Althoefer & L Seneviratne)
• Evolutionary Computation and Applications: Restoration of Half-toned Color-quantized Images using Particle Swarm Optimization with Multi-wavelet Mutation (F H F Leung)
• Comparison of GP and PSO on Polynomial Modeling (K Y Chan & T S Dillon).
• (source: Nielsen Book Data)

This book focuses on computational intelligence techniques and its applications - fast-growing and promising research topics that have drawn a great deal of attention from researchers over the years. It brings together many different aspects of the current research on intelligence technologies such as neural networks, support vector machines, fuzzy logic and evolutionary computation, and covers a wide range of applications from pattern recognition and system modeling, to intelligent control problems and biomedical applications. Fundamental concepts and essential analysis of various computational techniques are presented to offer a systematic and effective tool for better treatment of different applications, and simulation and experimental results are included to illustrate the design procedure and the effectiveness of the approaches.
(source: Nielsen Book Data)

• Agent and Multiagent Systems.- A Comparative Study between Human-Human Interaction and Human-Robot Interaction.- Dialogue and Argumentation in Multi-agent Diagnosis.- Reinforcement Q-Learning and Neural Networks to Acquire Negotiation Behaviors.- getALife - An Artificial Life Environment for the Evaluation of Agent-Based Systems and Evolutionary Algorithms for Reinforcement Learning.- An Approach to Efficient Trading Model of Hybrid Traders Based on Volume Discount.- Improving the Efficiency of Low-Level Decision Making in Robosoccer Using Boosted SVM.- Personal Assistants and Recommender Systems.- Closed Pattern Mining for the Discovery of User Preferences in a Calendar Assistant.- An Implementation of Goal-Oriented Fashion Recommendation System.- A Proposal on Recommender System Based on Observing Web-Chatting.- Ontological Query Processing and Maintaining Techniques for FAQ Systems.- On Human Resource Adaptability in an Agent-Based Virtual Organization.- Knowledge Modelling and Processing.- On the Pursuit of a Standard Language for Object-Oriented Constraint Modeling.- A Layered Ontology-Based Architecture for Integrating Geographic Information.- Generalizing the QSQR Evaluation Method for Horn Knowledge Bases.- On Vowels Segmentation and Identification Using Formant Transitions in Continuous Recitation of Quranic Arabic.- Adaptation of FCANN Method to Extract and Represent Comprehensible Knowledge from Neural Networks.- Video Similarity Measurement Based on Attributed Relational Graph Matching.- A Knowledge-Based System for CMM Evaluation.- Gating Artificial Neural Network Based Soft Sensor.- A Classification Method of Users Opinions Using Category-Based Dictionary Generated from Answers in Open-Ended Questionnaire System.- Training of Classifiers for the Recognition of Musical Instrument Dominating in the Same-Pitch Mix.- Intelliengence Technologies in Optimization and Combinatorial Problems.- Impact of Fuzzy Logic in the Cooperation of Metaheuristics.- An OCL-Based CSP Specification and Solving Tool.- Effects of At-Home Nursing Service Scheduling in Multiagent Systems.- Greedy and Exact Algorithms for Invitation Planning in Cancer Screening.- A Comparison of Three Meta-heuristics for a Closed-Loop Layout Problem with Unequal-Sized Facilities.- A Genetic Algorithm with Multiple Operators for Solving the Terminal Assignment Problem.- An Efficient Hybrid Method for an Expected Maximal Covering Location Problem.- Multi-sided Matching Lecture Allocation Mechanism.- AlineaGA: A Genetic Algorithm for Multiple Sequence Alignment.- Investigation of Strategies for the Generation of Multiclass Support Vector Machines.- Intelliengence Technologies in Computer and Telecommunication Systems.- Multiagent Monitoring System for Complex Network Infrastructure.- Multiagent Approach to Autonomous Reorganization of Monitoring Task Delegation in Distributed IDS.- An Intelligent Service Strategy in Linked Networks with Blocking and Feedback.- Advances in Automated Source-Level Debugging of Verilog Designs.- Spyware Prevention by Classifying End User License Agreements.- An Application of LS-SVM Method for Clustering in Wireless Sensor Networks.
• (source: Nielsen Book Data)

To built intelligent systems that can cope with real world problems we need to - velop computational mechanisms able to deal with very large amounts of data, gen- ate complex plans, schedules, and resource allocation strategies, re-plan their actions in real time, provide user friendly communication for human-device interactions, and perform complex optimization problems. In each of these tasks intelligence techno- gies play an important role, providing designers and creators with effective and adequate computational models. The field of intelligence technologies covers a variety of computational approaches that are often suggested and inspired by biological systems, exhibiting functional richness and flexibility of their natural behavior. This class of technologies consists of such important approaches as data mining algorithms, neural networks, genetic al- rithms, fuzzy and multi-valued logics, rough sets, agent-oriented computation, often integrated into complex hybrid solutions. Intelligence technologies are used to built machines that can act and think like living systems, solve problems in an autonomous way, develop rich private knowledge bases and produce results not foreseen and programmed in a direct way by designers and creators.
(source: Nielsen Book Data)

• What Is Computational Intelligence and Where Is It Going?.- New Millennium AI and the Convergence of History.- The Challenges of Building Computational Cognitive Architectures.- Programming a Parallel Computer: The Ersatz Brain Project.- The Human Brain as a Hierarchical Intelligent Control System.- Artificial Brain and OfficeMate TR based on Brain Information Processing Mechanism.- Natural Intelligence and Artificial Intelligence: Bridging the Gap between Neurons and Neuro-Imaging to Understand Intelligent Behaviour.- Computational Scene Analysis.- Brain-, Gene-, and Quantum Inspired Computational Intelligence: Challenges and Opportunities.- The Science of Pattern Recognition. Achievements and Perspectives.- Towards Comprehensive Foundations of Computational Intelligence.- Knowledge-Based Clustering in Computational Intelligence.- Generalization in Learning from Examples.- A Trend on Regularization and Model Selection in Statistical Learning: A Bayesian Ying Yang Learning Perspective.- Computational Intelligence in Mind Games.- Computer Go: A Grand Challenge to AI.- Noisy Chaotic Neural Networks for Combinatorial Optimization.
• (source: Nielsen Book Data)

In recent years computational intelligence has been extended by adding many other subdisciplines and this new field requires a series of challenging problems that will give it a sense of direction in order to ensure that research efforts are not wasted. This book written by top experts in computational intelligence provides such clear directions and a much-needed focus on the most important and challenging research issues.
(source: Nielsen Book Data)

• Intelligent computing everywhere / Alfons Schuster
• Infinitely complex machines / Eric Steinhart
• The nonclassical mind : cognitive science and nonclassical computing / Colin G. Johnson
• A computing model combining artificial neural networks and Petri nets / Alfons Schuster
• Quantum mechanics and artificial intelligence / Subhash Kak
• Quantum mechanics, computers, and the mind / David H. Glass, Mark McCartney
• Restoration of movement and thought from neuroelectric and metabolic brain activity : brain-computer interfaces (BCIs) / Niels Birbaumer, Klaus Haagen
• Computational neuroscience and cognitive brain functions / Gustavo Deco, Edmund T. Rolls
• GeneSim intelligent IT platform for the biomedical world / Martin Stetter, Andreas Nägele, Mathäus Dejori
• Artificial intelligence and DNA computing / Zoheir Ezziane
• Ambient intelligence : the confluence of ubiquitous/pervasive computing and artificial intelligence / Juan Carlos Augusto
• Artificial intelligence for space applications / Daniela Girimonte, Dario Izzo.

Intelligent Computing Everywhere reflects the current perception in various fields that modern computing applications are becoming increasingly challenged in terms of complexity and intelligence. It investigates the relevance and relationship artificial intelligence maintains with "modern strands of computing" i.e. pervasive computing and ambient intelligence, bioinformatics, neuroinformatics, computing and the mind, non-classical computing and novel computing models, as well as DNA computing and quantum computing. Each subject is examined from two main viewpoints, the first provides a state of the art introduction to a field such as DNA computing and the second investigates the subject from an artificial intelligence perspective. .
(source: Nielsen Book Data)

• A Quest for Granular Computing and Logic Processing (W Pedrycz)
• Abstraction and Linguistic Analysis of Conventional Numerical Dynamic Systems (F-Y Wang)
• Slicing: A Distributed Learning Approach (S A Eschrich & L O Hall)
• Marginal Learning Algorithms in Statistical Machine Learning (Q Tao & J Wang)
• Constraint Handling in Genetic Algorithm for Optimization (G G Yen)
• Hybrid PSO-EA Algorithm for Training Feedforward and Recurrent Neural Networks for Challenging Problems (X Cai et al.)
• Modular Wavelet-Fuzzy Networks (Y Lin & F-Y Wang)
• Ant Colony Algorithms: The State-of-the-Art (J Zhang et al.)
• Motif Discoveries in DNA and Protein Sequences Using Self-Organizing Neural Networks (D Liu & X Xiong)
• Computational Complexities of Combinatorial Problems with Applications to Reverse Engineering of Biological Networks (P Berman et al.)
• Advances in Fingerprint Recognition Algorithms with Application (J Tian et al.)
• Adaptation and Predictive Control Observed in Neuromuscular Control Systems (J He)
• Robust Adaptive Approximation Based Backstepping via Localized Adaptive Bounding (Y Zhao & J A Farrell)
• Dynamically Connected Fuzzy Single Input Rule Modules and Application to Underactuated Systems (J Yi et al.).
• (source: Nielsen Book Data)

Computational Intelligence (CI) is a recently emerging area in fundamental and applied research, exploiting a number of advanced information processing technologies that mainly embody neural networks, fuzzy logic and evolutionary computation. With a major concern to exploiting the tolerance for imperfection, uncertainty, and partial truth to achieve tractability, robustness and low solution cost, it becomes evident that composing methods of CI should be working concurrently rather than separately. It is this conviction that research on the synergism of CI paradigms has experienced significant growth in the last decade with some areas nearing maturity while many others remaining unresolved. This book systematically summarizes the latest findings and sheds light on the respective fields that might lead to future breakthroughs.
(source: Nielsen Book Data)

• 1. Three Generations of Coevolutionary Robotics / Jordan B. Pollack, Hod Lipson, Pablo Funes, Gregory Hornby 1
• 2. Beyond 2001: The Linguistic Spatial Odyssey / James M. Keller, Pascal Matsakis, Marjorie Skubic 11
• 3. Computing Machinery and Intelligence Amplification / Steven K. Rogers, Matthew Kabrisky, Kenneth Bauer, Mark E. Oxley 25
• 4. Visualizing Complexity in the Brain / Lloyd Watts 45
• 5. Emerging Technologies: Onr's Need for Intelligent Computation in Underwater Sensors / James F. McEachern, Robert T. Miyamoto 57
• 6. Beyond Volterra and Wiener: Optimal Modeling of Nonlinear Dynamical Systems in a Neural Space for Applications in Computational Intelligence / Rui J.P. de Figueiredo 65
• 7. Techniques for Extracting Classification and Regression Rules from Artificial Neural Networks / Rudy Setiono 99
• 8. Neural Networks for Control: Research Opportunities and Recent Developments / Paul J. Werbos 115
• 9. Intelligent Learning Robotic Systems Using Computational Intelligence / Toshio Fukuda, Naoyuki Kubota 121
• 10. Computational Intelligence in Logistics / Hans-Jurgen Zimmermann 139
• 11. Two New Convergence Results for Alternating Optimization / James C. Bezdek, Richard J. Hathaway 149
• 12. Constructive Design of a Discrete-Time Fuzzy Controller Based on Piecewise-Lyapunov Functions / Gang Feng, Dong Sun, Louis Wang 165
• 13. Evolutionary Computation and Cognitive Science / Janet Wiles, Jennifer Hallinan 179
• 14. Evolvable Hardware and Its Applications / T. Higuchi, E. Takahashi, Y. Kasai, T. Itatani, M. Iwata, H. Sakanashi, M. Murakawa, I. Kajitani, H. Nosato 191
• 15. Humanized Computational Intelligence with Interactive Evolutionary Computation / Hideyuki Takagi 207
• 16. Unsupervised Learning by Artificial Neural Networks / Harold Szu 219
• 17. Collective Intelligence / David H. Wolpert 245
• 18. Backpropagation: General Principles and Issues for Biology / Paul J. Werbos 261.

This is the definitive survey of computational intelligence from luminaries in the field. Computational intelligence is a fast moving, multidisciplinary field the nexus of diverse technical interest areas that include neural networks, fuzzy logic, and evolutionary computation. Keeping up with computational intelligence means understanding how it relates to an ever expanding range of applications. This is the book that ties it all together and puts that understanding well within your reach. In "Computational Intelligence: The Experts Speak", editors David B. Fogel and Charles J. Robinson present an unmatched compilation of expanded papers from plenary and special lecturers attending the 2002 IEEE World Congress on Computational Intelligence. Collectively, these papers provide a compelling snapshot of the issues that define the industry, as observed by some of the top minds in the computational intelligence community. In a series of topical chapters, this comprehensive volume shows how current technology is shaping computational intelligence, and it delivers eye opening insights into the field's future challenges. The research detailed here covers an array of leading edge applications, from coevolutionary robotics to underwater sensors and cognitive science, in such areas as: self organizing systems; situation awareness; human machine interaction; automatic control; and data recognition. "Computational Intelligence" also includes introductions to each grouping of contributions that provide helpful tutorials and discuss important parallels between topics. Whatever your role might be in this dynamic, influential field, this is the one reference that no practitioner of computational intelligence should be without.
(source: Nielsen Book Data)

• Intro
• Preface
• Organization
• Program Committee Chairs
• Program Committee Members
• Reviewers
• Contents
• Development of Energy Efficient Routing Protocol for Lifespan Optimization in Wireless Sensor Networks (EERP)
• 1 Introduction
• 2 Literature Review
• 3 Methodology and Proposed System
• 3.1 Cluster Head Selection and Data Transmission
• 4 Results and Discussions
• 5 Conclusion
• References
• Sentiment Analysis Using Social Media and Product Reviews
• 1 Introduction
• 2 Related Work
• 3 Methodology
• 3.1 Naïve Bayes Classifier

• 3.2 Support Vector Machine Classifier
• 3.3 Logistic Regression
• 4 Result and Discussion
• 5 Conclusion
• References
• A Stable Model for Learning and Memorization in Over-Parameterized Networks
• 1 Introduction
• 2 Related Work
• 3 Experimental Setup
• 4 Results
• 5 Conclusion
• References
• Analysis of Depth Sensing and Lane Detection Algorithms for Advanced Driver Assistance Systems
• 1 Introduction
• 1.1 Background
• 2 Proposed Strategy
• 2.1 Depth Estimation
• 2.1.1 Image Segmentation and Object Detection-Based Hybridized Approach
• 2.1.2 Pix2Pix Approach
• 2.1.3 U-Net

• 2.1.4 U-Net Backbones
• 2.1.5 U-Net ++
• 2.1.6 U-Net
• 3 Results
• 4 Conclusion
• References
• Implementation of E-Commerce Application with Analytics
• 1 Introduction
• 2 Related Work/Literature Survey
• 2.1 Purpose
• 2.2 Interactive Web Interface for Association Rule Mining and Medical Applications
• 2.3 Wet Experiment Preparation
• 2.4 Methodology
• 3 Count++
• 4 Result
• 4.1 Unsupervised Learning
• 4.2 Pattern Forecast Process
• 4.2.1 Accuracy
• 4.2.2 Customer Segmentation Using Data Mining Techniques
• 5 Conclusion
• References

• A Survey on the Latest Intrusions and Their Detection Systems in IoT-Based Network
• 1 Introduction
• 2 Motivation and Contributions
• 3 Architecture of IoT
• 3.1 IoT Protocols and Standards
• 3.1.1 IoT Data Protocols
• 3.1.2 Network Protocols for the IoT
• 4 IoT Vulnerabilities, Security Threats, and Attacks
• 4.1 Vulnerabilities
• 4.2 Security Threats and Attacks in IoT Paradigm
• 4.3 Security Concern Due to Threats and Attacks in IoT Networks
• 5 Solutions
• 6 Conclusion
• References
• Design and Analysis of Z-Source Inverter with Maximum Constant Boost Control Method

• 1 Introduction
• 2 Z-Source Inverter
• 2.1 Schematic Diagram
• 2.2 Operating Principle
• 2.3 Circuit Diagram for Different Operations and Analysis
• 3 Maximum Constant Boost Control
• 4 Simulation Results
• 4.1 Figures and Tables
• 5 Conclusion
• References
• SPV/Wind Energy-Based Hybrid Grid-Connected System with Optimum Power Flow Operation
• 1 Introduction
• 2 Various Standards
• 3 Grid-Connected Hybrid System Topology
• 3.1 Solar Model
• 3.2 Wind Model
• 3.3 MPPT of Solar and Wind
• 3.4 Inverter Bridge Model
• 3.5 Grid Synchronization
• 3.5.1 AANF
• 3.5.2 SOGI-PLL

Computational intelligence consists of those techniques that imitate the human brain and nature to adopt the decision-making approach. This book contains selected papers from the 8th International Conference on Computers, Management and Mathematical Sciences (ICCM) 2022 about fuzzy systems, neural networks and evolutionary computation that can address stochastic environments where reasoning is a significant attribute to derive potential solutions and focus on the business domain's computational aspects. This is a conference proceedings for scholars/students who are using the powerful algorithms, concepts and principles of computational intelligence in a wide spectrum of research cases.

• Text Summarization Approaches under Transfer Learning and Domain Adaptation Settings - A Survey.- An Effective Eye-Blink Based Cyber Secure PIN Password Authentication System.- A Comparison of Algorithms for Bayesian Network Learning for Triple Word Form Theory.- Application of Machine Learning Algorithm in Identification of Anaemia Diseases.- Detection of Fruits Image Applying Decision Tree Classifier Techniques.
• (source: Nielsen Book Data)

The book presents high-quality research papers presented at the International Conference on Computational Intelligence and Data Analytics (ICCIDA 2022), organized by the Department of Information Technology, Vasavi College of Engineering, Hyderabad, India in January 2022. ICCIDA provides an excellent platform for exchanging knowledge with the global community of scientists, engineers, and educators. This volume covers cutting-edge research in two prominent areas - computational intelligence and data analytics, and allied research areas.
(source: Nielsen Book Data)

This book is a compilation of accepted papers presented at the International Conference on Computing, Intelligence and Data Analytics (ICCIDA) in 2022 organized by Information Systems Engineering of the Kocaeli University, Turkey on September 16-17, 2022. The book highlights some of the latest research advances and cutting-edge analyses of real-world problems related to Computing, Intelligence and Data Analytics and their applications in various domains. This includes state of the art models and methods used on benchmark datasets.

• Development of UAV Deployment System using Split Ring Compound Planetary Gear System.- Factors influencing the development of digital citizenship on social media platforms: Narrative review.- A Policy Framework for Improving E-Waste Management in Bangladesh.- Impact of Financial Inclusion on Social and Economic Wellbeing of households: A Case of Kaski District, Nepal.- Minimizing E-Waste Through Improved Virtualization.- A Hybrid Hotel Recommendation Using Collaborative, Content Based and Knowledge Based approach.- Training Tracker: A Training Management System.- Analysis and Forecasting of Final Household Expenditure in South Africa Using Box-Jenkins - ARIMA Model.
• (source: Nielsen Book Data)

This book of Springer Nature is another proof of Springer's outstanding and greatness on the lively interface of Smart Computational Optimization, Green ICT, Smart Intelligence and Machine Learning! It is a Master Piece of what our community of academics and experts can provide when an Interconnected Approach of Joint, Mutual and Meta Learning is supported by Modern Operational Research and Experience of the World-Leader Springer Nature! The 5th edition of International Conference on Intelligent Computing and Optimization took place at October 27-28, 2022, via Zoom. Objective was to celebrate "Creativity with Compassion and Wisdom" with researchers, scholars, experts and investigators in Intelligent Computing and Optimization across the planet, to share knowledge, experience, innovation-a marvelous opportunity for discourse and mutuality by novel research, invention and creativity. This proceedings book of ICO'2022 is published by Springer Nature-Quality Label of wonderful. .
(source: Nielsen Book Data)