This book constitutes the proceedings of the Third International Conference on Computational Intelligence, Cyber Security, and Computational Models, ICC3 2017, which was held in Coimbatore, India, in December 2017. The 15 papers presented in this volume were carefully reviewed and selected from 63 submissions. They were organized in topical sections named: computational intelligence; cyber security; and computational models.

This book includes papers presented at SOCO 2018, CISIS 2018 and ICEUTE 2018, all held in the beautiful and historic city of San Sebastian (Spain), in June 2018. Soft computing represents a collection or set of computational techniques in machine learning, computer science and some engineering disciplines, which investigate, simulate, and analyze highly complex issues and phenomena. After a rigorous peer-review process, the 13th SOCO 2018 International Program Committee selected 41 papers, with a special emphasis on optimization, modeling and control using soft computing techniques and soft computing applications in the field of industrial and environmental enterprises. The aim of the 11th CISIS 2018 conference was to offer a meeting opportunity for academic and industry researchers from the vast areas of computational intelligence, information security, and data mining. The need for intelligent, flexible behaviour by large, complex systems, especially in mission-critical domains, was the catalyst for the overall event.Eight of the papers included in the book were selected by the CISIS 2018 International Program Committee. The International Program Committee of ICEUTE 2018 selected 11 papers for inclusion in these conference proceedings.

This volume of Advances in Intelligent and Soft Computing contains accepted papers presented at SOCO 2016, CISIS 2016 and ICEUTE 2016, all conferences held in the beautiful and historic city of San Sebastian (Spain), in October 2016. Soft computing represents a collection or set of computational techniques in machine learning, computer science and some engineering disciplines, which investigate, simulate, and analyze very complex issues and phenomena. After a through peer-review process, the 11th SOCO 2016 International Program Committee selected 45 papers. In this relevant edition a special emphasis was put on the organization of special sessions. Two special session was organized related to relevant topics as: Optimization, Modeling and Control Systems by Soft Computing and Soft Computing Methods in Manufacturing and Management Systems. The aim of the 9th CISIS 2016 conference is to offer a meeting opportunity for academic and industry-related researchers belonging to the various, vast communities of Computational Intelligence, Information Security, and Data Mining. The need for intelligent, flexible behaviour by large, complex systems, especially in mission-critical domains, is intended to be the catalyst and the aggregation stimulus for the overall event. After a through peer-review process, the CISIS 2016 International Program Committee selected 20 papers. In the case of 7th ICEUTE 2016, the International Program Committee selected 14 papers.

In recent years, ELM has emerged as a revolutionary technique of computational intelligence, and has attracted considerable attentions. An extreme learning machine (ELM) is a single layer feed-forward neural network alike learning system, whose connections from the input layer to the hidden layer are randomly generated, while the connections from the hidden layer to the output layer are learned through linear learning methods. The outstanding merits of extreme learning machine (ELM) are its fast learning speed, trivial human intervene and high scalability. This book contains some selected papers from the International Conference on Extreme Learning Machine 2013, which was held in Beijing China, October 15-17, 2013. This conference aims to bring together the researchers and practitioners of extreme learning machine from a variety of fields including artificial intelligence, biomedical engineering and bioinformatics, system modelling and control, and signal and image processing, to promote research and discussions of “learning without iterative tuning". This book covers algorithms and applications of ELM. It gives readers a glance of the newest developments of ELM.

In recent years, ELM has emerged as a revolutionary technique of computational intelligence, and has attracted considerable attentions. An extreme learning machine (ELM) is a single layer feed-forward neural network alike learning system, whose connections from the input layer to the hidden layer are randomly generated, while the connections from the hidden layer to the output layer are learned through linear learning methods. The outstanding merits of extreme learning machine (ELM) are its fast learning speed, trivial human intervene and high scalability.

This book contains some selected papers from the International Conference on Extreme Learning Machine 2013, which was held in Beijing China, October 15-17, 2013. This conference aims to bring together the researchers and practitioners of extreme learning machine from a variety of fields including artificial intelligence, biomedical engineering and bioinformatics, system modelling and control, and signal and image processing, to promote research and discussions of learning without iterative tuning."

This book covers algorithms and applications of ELM. It gives readers a glance of the newest developments of ELM."

This book contains cutting-edge research material presented by researchers, engineers, developers, and practitioners from academia and industry at the International Conference on Computational Intelligence, Cyber Security and Computational Models (ICC3) organized by PSG College of Technology, Coimbatore, India during December 19-21, 2013. The materials in the book include theory and applications to provide design, analysis, and modeling of the key areas. The book will be useful material for students, researchers, professionals, as well academicians in understanding current research trends and findings and future scope of research in computational intelligence, cyber security, and computational models.

The two LNAI volumes 7208 and 7209 constitute the proceedings of the 7th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2012, held in Salamanca, Spain, in March 2012. The 118 papers published in these proceedings were carefully reviewed and selected from 293 submissions. They are organized in topical sessions on agents and multi agents systems, HAIS applications, cluster analysis, data mining and knowledge discovery, evolutionary computation, learning algorithms, systems, man, and cybernetics by HAIS workshop, methods of classifier fusion, HAIS for computer security (HAISFCS), data mining: data preparation and analysis, hybrid artificial intelligence systems in management of production systems, hybrid artificial intelligent systems for ordinal regression, hybrid metaheuristics for combinatorial optimization and modelling complex systems, hybrid computational intelligence and lattice computing for image and signal processing and nonstationary models of pattern recognition and classifier combinations.

The two LNAI volumes 7208 and 7209 constitute the proceedings of the 7th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2012, held in Salamanca, Spain, in March 2012. The 118 papers published in these proceedings were carefully reviewed and selected from 293 submissions. They are organized in topical sessions on agents and multi agents systems, HAIS applications, cluster analysis, data mining and knowledge discovery, evolutionary computation, learning algorithms, systems, man, and cybernetics by HAIS workshop, methods of classifier fusion, HAIS for computer security (HAISFCS), data mining: data preparation and analysis, hybrid artificial intelligence systems in management of production systems, hybrid artificial intelligent systems for ordinal regression, hybrid metaheuristics for combinatorial optimization and modelling complex systems, hybrid computational intelligence and lattice computing for image and signal processing and nonstationary models of pattern recognition and classifier combinations.

This book is a composition of diverse points of view regarding the application of Computational Intelligence techniques and methods into Remote Sensing data and problems. It is the general consensus that classi?cation, and related data processing, and global optimization methods are the main topics of Compu- tional Intelligence. Global random optimization algorithms appear in this book, such as the Simulated Annealing in chapter 6 and the Genetic Algorithms p- posedinchapters3and9. Muchofthecontentsofthe bookaredevotedto image segmentationandrecognition, using diversetoolsfromregionsofComputational Intelligence, ranging from Arti?cial Neural Networks to Markov Random Field modelling. However, there are some fringe topics, such the parallel implem- tation of some algorithms or the image watermarking that make evident that thefrontiersbetweenComputationalIntelligenceandneighboringcomputational disciplines are blurred and the fences run low and full of holes in many places. The book starts with a review of the current designs of hyperspectral sensors, more appropriately named Imaging Spectrometers. Knowing the shortcomings and advantages of the diverse designs may condition the results on some app- cations of Computational Intelligence algorithms to the processing and und- standing of them Remote Sensing images produced by these sensors. Then the book contentsmovesinto basic signalprocessing techniquessuch ascompression and watermarking applied to remote sensing images. With the huge amount of remotesensinginformationandtheincreasingrateatwhichitisbeingproduced, itseems only naturalthatcompressiontechniques willleapintoa prominentrole in the near future, overcoming the resistances of the users against uncontrolled manipulation of "their" data. Watermarkingis the way to address issues of o- ership authentication in digital contents.

The book presents an overview of current research on biologically inspired autonomous robotics from the perspective of some of the most relevant researchers in this area. The book crosses several boundaries in the field of robotics and the closely related field of artificial life. The key aim throughout the book is to obtain autonomy at different levels. From the basic motor behavior in some exotic robot architectures right through to the planning of complex behaviors or the evolution of robot control structures, the book explores different degrees and definitions of autonomous behavior. These behaviors are supported by a wide variety of modeling techniques: structural grammars, neural networks, and fuzzy logic and evolution underlies many of the development processes. Thus this text can be used by scientists and students interested in these areas and provides a general view of the field for a more general audience.

Provides a broad sample of current information processing applications

Includes examples of successful applications that will encourage practitioners to apply the techniques described in the book to real-life problems

This book is a composition of diverse points of view regarding the application of Computational Intelligence techniques and methods into Remote Sensing data and problems. It is the general consensus that classi?cation, and related data processing, and global optimization methods are the main topics of Compu- tional Intelligence. Global random optimization algorithms appear in this book, such as the Simulated Annealing in chapter 6 and the Genetic Algorithms p- posedinchapters3and9. Muchofthecontentsofthe bookaredevotedto image segmentationandrecognition, using diversetoolsfromregionsofComputational Intelligence, ranging from Arti?cial Neural Networks to Markov Random Field modelling. However, there are some fringe topics, such the parallel implem- tation of some algorithms or the image watermarking that make evident that thefrontiersbetweenComputationalIntelligenceandneighboringcomputational disciplines are blurred and the fences run low and full of holes in many places. The book starts with a review of the current designs of hyperspectral sensors, more appropriately named Imaging Spectrometers. Knowing the shortcomings and advantages of the diverse designs may condition the results on some app- cations of Computational Intelligence algorithms to the processing and und- standing of them Remote Sensing images produced by these sensors. Then the book contentsmovesinto basic signalprocessing techniquessuch ascompression and watermarking applied to remote sensing images. With the huge amount of remotesensinginformationandtheincreasingrateatwhichitisbeingproduced, itseems only naturalthatcompressiontechniques willleapintoa prominentrole in the near future, overcoming the resistances of the users against uncontrolled manipulation of "their" data. Watermarkingis the way to address issues of o- ership authentication in digital contents.

This book constitutes the refereed proceedings of the 9th International Work-Conference on Artificial Neural Networks, IWANN 2007, held in San Sebastian, Spain in June 2007.

The 145 revised full papers presented together with 3 invited lectures were carefully reviewed and selected from over 260 submissions. The papers are organized in thematic sections on theoretical concepts and neurocomputational formulations, inmproving models and learning procedures, self-organizing networks, kernel methods, evolutionary and genetic algorithms, evolutionary learning, fuzzy systems, neuroengineering and hardware implementations, data analysis, signal processing, speech processing, images processing, time series and prediction, robotics and planning motor control, power system applications, internet and web applications, biomedical applications, neural networks and other machine learning methods in cancer research, assistive technologies and e-health, as well as other applications.

The book presents an overview of current research on biologically inspired autonomous robotics from the perspective of some of the most relevant researchers in this area. The book crosses several boundaries in the field of robotics and the closely related field of artificial life. The key aim throughout the book is to obtain autonomy at different levels. From the basic motor behavior in some exotic robot architectures right through to the planning of complex behaviors or the evolution of robot control structures, the book explores different degrees and definitions of autonomous behavior. These behaviors are supported by a wide variety of modeling techniques: structural grammars, neural networks, and fuzzy logic and evolution underlies many of the development processes. Thus this text can be used by scientists and students interested in these areas and provides a general view of the field for a more general audience.

This book constitutes the proceedings of the 4th International Conference on Computational Intelligence, Cyber Security, and Computational Models, ICC3 2019, which was held in Coimbatore, India, in December 2019. The 9 papers presented in this volume were carefully reviewed and selected from 38 submissions. They were organized in topical sections named: computational intelligence; cyber security; and computational models.

Provides a broad sample of current information processing applications

Includes examples of successful applications that will encourage practitioners to apply the techniques described in the book to real-life problems

This book constitutes the refereed proceedings of the 16th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2012, held in San Sebastian, Spain, in September 2012.
The 20 revised full papers presented were carefully reviewed and selected from 130 submissions. The papers are organized in topical sections on bioinspired and machine learning methods, machine learning applications, semantics and ontology based techniques, and lattice computing and games.