This volume of Advances in Intelligent and Soft Computing contains accepted papers presented at SOCO 2014, CISIS 2014 and ICEUTE 2014, all conferences held in the beautiful and historic city of Bilbao (Spain), in June 2014. 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 9th SOCO 2014 International Program Committee selected 31 papers which are published in these conference proceedings. In this relevant edition a special emphasis was put on the organization of special sessions. One special session was organized related to relevant topics as: Soft Computing Methods in Manufacturing and Management Systems. The aim of the 7th CISIS 2014 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 2014 International Program Committee selected 23 papers and the 5th ICEUTE 2014 International Program Committee selected 2 papers which are published in these conference proceedings as well.

This volume includes papers presented at SOCO 2017, CISIS 2017, and ICEUTE 2017, all conferences held in the beautiful and historic city of León (Spain) in September 2017. Soft computing represents a collection of computational techniques in machine learning, computer science, and some engineering disciplines, which investigate, simulate, and analyze highly complex issues and phenomena. These proceeding s feature 48 papers from the 12th SOCO 2017, covering topics such as artificial intelligence and machine learning applied to health sciences; and soft computing methods in manufacturing and management systems. The book also presents 18 papers from the 10th CISIS 2017, which provided a platform for researchers from the fields of computational intelligence, information security, and data mining to meet and discuss the need for intelligent, flexible behavior by large, complex systems, especially in mission-critical domains. It addresses various topics, like identification, simulation and prevention of security and privacy threats in modern communication networks Furthermore, the book includes 8 papers from the 8th ICEUTE 2017. The selection of papers for all three conferences was extremely rigorous in order to maintain the high quality and we would like to thank the members of the Program Committees for their hard work in the reviewing process.

This volume of Advances in Intelligent and Soft Computing contains accepted papers presented at the 8th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2015) and the 6th International Conference on European Transnational Education (ICEUTE 2015). These conferences were held in the beautiful and historic city of Burgos (Spain), in June 2015. The aim of the 8th CISIS 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 2015 International Program Committee selected 43 papers, written by authors from 16 different countries. In the case of 6th ICEUTE conference, the International Program Committee selected 12 papers (from 7 countries). These papers are published in present conference proceedings, achieving an acceptance rate of about 39%. The selection of papers was extremely rigorous in order to maintain the high quality of the conference and we would like to thank the members of the Program Committees for their hard work in the reviewing process. This is a crucial process to the creation of a high standard conference and the CISIS and ICEUTE conferences would not exist without their help.

This volume of Advances in Intelligent and Soft Computing contains accepted papers presented at the 10th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2015), held in the beautiful and historic city of Burgos (Spain), in June 2015. 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. This Conference is mainly focused on its industrial and environmental applications. After a through peer-review process, the SOCO 2015 International Program Committee selected 41 papers, written by authors from 15 different countries. These papers are published in present conference proceedings, achieving an acceptance rate of 40%. The selection of papers was extremely rigorous in order to maintain the high quality of the conference and we would like to thank the members of the International Program Committees for their hard work during the review process. This is a crucial issue for creation of a high standard conference and the SOCO conference would not exist without their help.

This book constitutes the refereed proceedings of the workshops which complemented the 13th International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2015, held in Salamanca, Spain, in June 2015. The 36 revised full papers presented were carefully reviewed and selected from 91 submissions. This volume presents the papers that have been accepted for the following workshops: Workshop on Agents and multi-agent Systems for AAL and e-HEALTH, Workshop on Agent-Based Solutions for Manufacturing and Supply Chain, Workshop on MAS for Complex Networks and Social Computation, Workshop on Intelligent Systems for Context-based Information Fusion, Workshop on Multi-agent based Applications for Smart Grids and Sustainable Energy Systems, Workshop on Multiagent System based Learning Environments, Workshop in Intelligent Human-Agent Societies.

This book constitutes the refereed proceedings of the 16th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2015, held in Wroclaw, Poland, in October 2015. The 64 revised full papers presented were carefully reviewed and selected from 127 submissions. These papers provided a valuable collection of recent research outcomes in data engineering and automated learning, from methodologies, frameworks, and techniques to applications. In addition to various topics such as evolutionary algorithms, neural networks, probabilistic modeling, swarm intelligent, multi-objective optimization, and practical applications in regression, classification, clustering, biological data processing, text processing, video analysis, IDEAL 2015 also featured a number of special sessions on several emerging topics such as computational intelligence for optimization of communication networks, discovering knowledge from data, simulation-driven DES-like modeling and performance evaluation, and intelligent applications in real-world problems.

This monograph opens up new horizons for engineers and researchers in academia and in industry dealing with or interested in new developments in the field of system identification and control. It emphasizes guidelines for working solutions and practical advice for their implementation rather than the theoretical background of Gaussian process (GP) models. The book demonstrates the potential of this recent development in probabilistic machine-learning methods and gives the reader an intuitive understanding of the topic. The current state of the art is treated along with possible future directions for research. Systems control design relies on mathematical models and these may be developed from measurement data. This process of system identification, when based on GP models, can play an integral part of control design in data-based control and its description as such is an essential aspect of the text. The background of GP regression is introduced first with system identification and incorporation of prior knowledge then leading into full-blown control. The book is illustrated by extensive use of examples, line drawings, and graphical presentation of computer-simulation results and plant measurements. The research results presented are applied in real-life case studies drawn from successful applications including: a gas–liquid separator control; urban-traffic signal modelling and reconstruction; and prediction of atmospheric ozone concentration. A MATLAB® toolbox, for identification and simulation of dynamic GP models is provided for download.