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• On the Foundations and the Applications of Evolutionary Computing / Pierre Del Moral, Alexandru-Adrian Tantar and Emilia Tantar
• Incorporating Regular Vines in Estimation of Distribution Algorithms / Rogelio Salinas-Gutiérrez, Arturo Hernández-Aguirre and Enrique R. Villa-Diharce
• The Gaussian Polytree EDA with Copula Functions and Mutations / Ignacio Segovia Domínguez, Arturo Hernández Aguirre and Enrique Villa Diharce
• On Quality Indicators for Black-Box Level Set Approximation / Michael T.M. Emmerich, André H. Deutz and Johannes W. Kruisselbrink
• Set Oriented Methods for the Numerical Treatment of Multiobjective Optimization Problems / Oliver Schütze, Katrin Witting, Sina Ober-Blöbaum and Michael Dellnitz
• A Complex-Networks View of Hard Combinatorial Search Spaces / Marco Tomassini and Fabio Daolio
• Cooperative Coevolution for Agrifood Process Modeling / Olivier Barrière, Evelyne Lutton, Pierre-Henri Wuillemin, Cédric Baudrit and Mariette Sicard, et al.
• Hybridizing cGAs with PSO-like Mutation / E. Alba and A. Villagra
• On Gradient-Based Local Search to Hybridize Multi-objective Evolutionary Algorithms / Adriana Lara, Oliver Schütze and Carlos A. Coello Coello
• On the Integration of Theoretical Single-Objective Scheduling Results for Multi-objective Problems / Christian Grimme, Markus Kemmerling and Joachim Lepping
• Analysing the Robustness of Multiobjectivisation Approaches Applied to Large Scale Optimisation Problems / Carlos Segura, Eduardo Segredo and Coromoto León
• A Comparative Study of Heuristic Conversion Algorithms, Genetic Programming and Return Predictability on the German Market / Esther Mohr, Günter Schmidt and Sebastian Jansen.

The aim of this book is to provide a strong theoretical support for understanding and analyzing the behavior of evolutionary algorithms, as well as for creating a bridge between probability, set-oriented numerics and evolutionary computation. The volume encloses a collection of contributions that were presented at the EVOLVE 2011 international workshop, held in Luxembourg, May 25-27, 2011, coming from invited speakers and also from selected regular submissions. The aim of EVOLVE is to unify the perspectives offered by probability, set oriented numerics and evolutionary computation. EVOLVE focuses on challenging aspects that arise at the passage from theory to new paradigms and practice, elaborating on the foundations of evolutionary algorithms and theory-inspired methods merged with cutting-edge techniques that ensure performance guarantee factors. EVOLVE is also intended to foster a growing interest for robust and efficient methods with a sound theoretical background. The chapters enclose challenging theoretical findings, concrete optimization problems as well as new perspectives. By gathering contributions from researchers with different backgrounds, the book is expected to set the basis for a unified view and vocabulary where theoretical advancements may echo in different domains.
(source: Nielsen Book Data)

• Swarm Intelligence and Its Applications.- Operational Technologies and Networked Multimedia Applications.- Wearable Computing and Intelligent Data Hiding.- Image Processing and Intelligent Applications.- Intelligent Multimedia Tools and Applications.- Technologies for Next-Generation Network Environments.- Recent Progress in Computational Electromagnetic Dynamics.- Future Cyber Security, Privacy and Forensics for Advanced systems.- Data Mining Techniques and its Applications.- Optimization Models in Deep Learning/Machine Learning.
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This book contains selected papers presented at ICGEC 2021, the 14th International Conference on Genetic and Evolutionary Computing, held from October 21-23, 2021 in Jilin City, China. The conference was technically co-sponsored by Springer, Northeast Electric Power University Fujian University of Technology, Shandong University of Science and Technology, and Western Norway University of Applied Sciences. It is intended as an international forum for the researchers and professionals in all areas of genetic and evolutionary computing. And the readers may learn the up-to-date techniques of the mentioned topics, including swarm intelligence, artificial intelligence, information hiding and data mining techniques, which can help them to bring new ideas or apply the designed approaches from the collected papers to their professional jobs.
(source: Nielsen Book Data)

• Automated Flower Species Identification by using Deep convolution neural network
• Information Retrieval for Cloud Forensics
• Machine Translation System Combination with Enhanced Alignments using Word Embeddings
• Geometry Based Machining Feature Retrieval with Inductive Transfer Learning
• Grapheme to phoneme conversion for Malayalam Speech Using encoder-decoder Architecture
• Usage of Block Chain Technology in e-Voting System using Private Block Chain
• Bengali Visual Genome: A Multimodal Dataset for Machine Translation and Image Captioning
• Deep Learning based Mosquito Species detection using Wingbeats frequencies
• Developments in Capsule Network Architecture: A Review
• Computer aided segmentation of polyps using Mask R-CNN and approach to reduce false positives
• Image GPT with Super Resolution.

This book presents the proceedings of the 9th International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA 2021), held at NIT Mizoram, Aizwal, Mizoram, India, during June 25-26, 2021. FICTA conference aims to bring together researchers, scientists, engineers, and practitioners to exchange their new ideas and experiences in the domain of intelligent computing theories with prospective applications to various engineering disciplines. This volume covers broad areas of Intelligent Data Engineering and Analytics. The conference papers included herein presents both theoretical as well as practical aspects of data intensive computing, data mining, big data, knowledge management, intelligent data acquisition and processing from sensors, data communication networks protocols and architectures, etc. The volume will also serve as a knowledge centre for students of post-graduate level in various engineering disciplines. .

• Formal Theory
• New Techniques
• Experimental Analysis
• Multiobjective Optimization
• Hybrid Methods
• Applications.

This book constitutes the refereed proceedings of the 10th International Conference on Parallel Problem Solving from Nature, PPSN 2008, held in Dortmund, Germany, in September 2008. The 114 revised full papers presented were carefully reviewed and selected from 206 submissions. The conference covers a wide range of topics, such as evolutionary computation, quantum computation, molecular computation, neural computation, artificial life, swarm intelligence, artificial ant systems, artificial immune systems, self-organizing systems, emergent behaviors, and applications to real-world problems. The paper are organized in topical sections on formal theory, new techniques, experimental analysis, multiobjective optimization, hybrid methods, and applications.
(source: Nielsen Book Data)

• Heuristics I.- Alternative Solution Representations for the Job Shop Scheduling Problem in Ant Colony Optimisation.- Analyzing the Role of "Smart" Start Points in Coarse Search-Greedy Search.- Concealed Contributors to Result Quality - The Search Process of Ant Colony System.- Ants Guide Future Pilots.- Complex Systems I.- Information Transfer by Particles in Cellular Automata.- An Artificial Development Model for Cell Pattern Generation.- Rounds Effect in Evolutionary Games.- Modelling Architectural Visual Experience Using Non-linear Dimensionality Reduction.- An Evolutionary Benefit from Misperception in Foraging Behaviour.- Simulated Evolution of Discourse with Coupled Recurrent Networks.- How Different Hierarchical Relationships Impact Evolution.- A Dual Phase Evolution Model of Adaptive Radiation in Landscapes.- Biological Systems I.- Directed Evolution of an Artificial Cell Lineage.- An Integrated QAP-Based Approach to Visualize Patterns of Gene Expression Similarity.- Complement-Based Self-Replicated, Self-Assembled Systems (CBSRSAS).- Self-maintained Movements of Droplets with Convection Flow.- Structural Circuits and Attractors in Kauffman Networks.- The Effects of Learning on the Roles of Chance, History and Adaptation in Evolving Neural Networks.- Unsupervised Acoustic Classification of Bird Species Using Hierarchical Self-organizing Maps.- The Prisoner's Dilemma with Image Scoring on Networks: How Does a Player's Strategy Depend on Its Place in the Social Network?.- Heuristics II.- Population-Based Ant Colony Optimisation for Multi-objective Function Optimisation.- Mechanisms for Evolutionary Reincarnation.- An Evolutionary Algorithm with Spatially Distributed Surrogates for Multiobjective Optimization.- Examining Dissimilarity Scaling in Ant Colony Approaches to Data Clustering.- Complex Systems II.- A Framework for the Co-evolution of Genes, Proteins and a Genetic Code Within an Artificial Chemistry Reaction Set.- In-Formation Flocking: An Approach to Data Visualization Using Multi-agent Formation Behavior.- A Principled Approach to Swarm-Based Wall-Building.- Pattern Extraction Improves Automata-Based Syntax Analysis in Songbirds.- Heuristics III.- A Modified Strategy for the Constriction Factor in Particle Swarm Optimization.- A Differential Evolution Variant of NSGA II for Real World Multiobjective Optimization.- Investigating a Hybrid Metaheuristic for Job Shop Rescheduling.- Enhancements to Extremal Optimisation for Generalised Assignment.- Biological Systems II.- Identification of Marker Genes Discriminating the Pathological Stages in Ovarian Carcinoma by Using Support Vector Machine and Systems Biology.- Ancestral DNA Sequence Reconstruction Using Recursive Genetic Algorithms.
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This book constitutes the refereed proceedings of the Third Australian Conference on Artificial Life, ACAL 2007, held in Gold Coast, Australia, in December 2007. The 34 revised full papers presented were carefully reviewed and selected from 70 submissions. Research in Alife covers the main areas of biological behaviour as a metaphor for computational models, computational models that reproduce/duplicate a biological behaviour, and computational models to solve biological problems.
(source: Nielsen Book Data)

• Chapter 1: An Enhanced Model for Digital Reference Services (MDRS).-
• Chapter 2: Fuzzy Random Based Mean Variance Model For Agricultural Production Planning.-
• Chapter 3: Residual Neural Network vs Local Binary Convolutional Neural Networks for Bilingual Handwritten Digit Recognition.-
• Chapter 4: Incorporating the Markov Chain Model in WBSN for Improving Patients' Remote Monitoring Systems.-
• Chapter 5: Designing Deep Neural Network with Chicken Swarm Optimization for Violence Video Classification using VSD2014 Dataset.-
• Chapter 6: Header Based Email Spam Detection Framework Using Support Vector Machine (SVM) Technique.-
• Chapter 7: A Mechanism to Support Agile Frameworks Enhancing Reliability Assessment for SCS Development: A Case Study of Medical Surgery Departments.-
• Chapter 8: Link Bandwidth Recommendation for Indonesian E-Health Grid.-
• Chapter 9: Investigating the Optimal Parameterization of Deep Neural Network and Synthetic Data Workflow for Imbalance Liver Disorder Dataset Classification.-
• Chapter 10: Genetic Algorithm Based Parallel K-Means Data Clustering Algorithm Using MapReduce Programming Paradigm on Hadoop Environment (GAPKCA).-
• Chapter 11: Android Botnet Detection by Classification Techniques.
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This book provides an introduction to data science and offers a practical overview of the concepts and techniques that readers need to get the most out of their large-scale data mining projects and research studies. It discusses data-analytical thinking, which is essential to extract useful knowledge and obtain commercial value from the data. Also known as data-driven science, soft computing and data mining disciplines cover a broad interdisciplinary range of scientific methods and processes. The book provides readers with sufficient knowledge to tackle a wide range of issues in complex systems, bringing together the scopes that integrate soft computing and data mining in various combinations of applications and practices, since to thrive in these data-driven ecosystems, researchers, data analysts and practitioners must understand the design choice and options of these approaches. This book helps readers to solve complex benchmark problems and to better appreciate the concepts, tools and techniques used.
(source: Nielsen Book Data)

• AI Techniques and applications.- Data Analytics and Technologies.- Data Mining and Image Processing.- Machine & Statistical Learning. .
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This book constitutes the refereed proceedings of the 6th International Conference on Soft Computing in Data Science, SCDS 2021, which was held virtually in November 2021. The 31 revised full papers presented were carefully reviewed and selected from 79 submissions. The papers are organized in topical sections on AI techniques and applications; data analytics and technologies; data mining and image processing; machine & statistical learning. .
(source: Nielsen Book Data)