This book includes 57 papers presented at the SOCO 2019 conference held in the historic city of Seville (Spain), in May 2019. Soft computing represents a set of computational techniques in machine learning, computer science and various engineering disciplines, which investigate, simulate, and analyze very complex issues and phenomena. The selection of papers was extremely rigorous in order to maintain the high quality of the conference, which featured a number of special sessions, including sessions on: Soft Computing Methods in Manufacturing and Management Systems; Soft Computing Applications in the Field of Industrial and Environmental Enterprises; Optimization, Modeling and Control by Soft Computing Techniques; and Soft Computing in Aerospace, Mechanical and Civil Engineering: New methods and Industrial Applications.

This volume presents papers presented at CISIS 2019 and ICEUTE 2019, held in the beautiful and historic city of Seville (Spain) in May 2019. The 12th CISIS 2019 conference offered a meeting opportunity for academic and industry-related researchers form the various communities of computational intelligence, information security and data mining, and the need for intelligent, flexible behaviour by large, complex systems, especially in mission-critical domains, was the catalyst and the aggregation stimulus for the event. The book covers current topics such as cryptographic and data analytics solutions to fulfil least minimum privilege and endorse least minimum effort in information systems. The book also includes 15 papers from the 10th ICEUTE 2019, covering topics like new approaches to assess competencies and innovation in computer science education.

This book of Lecture Notes in Networks and Systems contains accepted papers presented at the 15th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2022) and the 13th International Conference on EUropean Transnational Education (ICEUTE 2022). These conferences were held in the beautiful city of Salamanca, Spain, in September 2022. The aim of the CISIS 2022 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 thorough peer review process, the CISIS 2022 International Program Committee selected 20 papers, which are published in this conference proceedings. In this edition, three special sessions were organized: Cybersecurity in Future Connected Societies, Cybersecurity and Trusted Supply Chains of ICT, and Intelligent Solutions for Cybersecurity Systems. The aim of ICEUTE 2022 is to offer a meeting point for people working on transnational education within Europe. It provides a stimulating and fruitful forum for presenting and discussing the latest works and advances on transnational education within European countries. In the case of ICEUTE 2022, the International Program Committee selected 5 papers, which are also published in this conference proceedings. The selection of papers was extremely rigorous to maintain the high quality of the conferences. We want to thank the members of the Program Committees for their hard work during the reviewing process. This is a crucial process for creating a high-standard conference; the CISIS and ICEUTE would not exist without their help.

This book contains accepted papers presented at SOCO 2022 conference held in the beautiful and historic city of Salamanca (Spain), in September 2022. 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 thorough peer-review process, the 17th SOCO 2022 International Program Committee selected 64 papers which are published in these conference proceedings and represent an acceptance rate of 60%. In this relevant edition, a particular emphasis was put on the organization of special sessions. Seven special sessions were organized related to relevant topics such as machine learning and computer vision in Industry 4.0; time series forecasting in industrial and environmental applications; optimization, modeling, and control by soft computing techniques; soft computing applied to renewable energy systems; preprocessing big data in machine learning; tackling real-world problems with artificial intelligence. The selection of papers was extremely rigorous to maintain the high quality of the conference. We want to thank the members of the program committees for their hard work during the reviewing process. This is a crucial process for creating a high-standard conference; the SOCO conference would not exist without their help.

This book constitutes the refereed proceedings of the 17th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2022, held in Salamanca, Spain, in September 2022. The 43 full papers presented in this book were carefully reviewed and selected from 67 submissions. They were organized in topical sections as follows: bioinformatics; data mining and decision support systems; deep learning; evolutionary computation; HAIS applications; image and speech signal processing; and optimization techniques.

With the development of Big Data platforms for managing massive amount of data and wide availability of tools for processing these data, the biggest limitation is the lack of trained experts who are qualified to process and interpret the results. This textbook is intended for graduate students and experts using methods of cluster analysis and applications in various fields. Suitable for an introductory course on cluster analysis or data mining, with an in-depth mathematical treatment that includes discussions on different measures, primitives (points, lines, etc.) and optimization-based clustering methods, Cluster Analysis and Applications also includes coverage of deep learning based clustering methods. With clear explanations of ideas and precise definitions of concepts, accompanied by numerous examples and exercises together with Mathematica programs and modules, Cluster Analysis and Applications may be used by students and researchers in various disciplines, working in data analysis or data science.

With the development of Big Data platforms for managing massive amount of data and wide availability of tools for processing these data, the biggest limitation is the lack of trained experts who are qualified to process and interpret the results. This textbook is intended for graduate students and experts using methods of cluster analysis and applications in various fields. Suitable for an introductory course on cluster analysis or data mining, with an in-depth mathematical treatment that includes discussions on different measures, primitives (points, lines, etc.) and optimization-based clustering methods, Cluster Analysis and Applications also includes coverage of deep learning based clustering methods. With clear explanations of ideas and precise definitions of concepts, accompanied by numerous examples and exercises together with Mathematica programs and modules, Cluster Analysis and Applications may be used by students and researchers in various disciplines, working in data analysis or data science.

This volume constitutes the refereed proceedings of the 11th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2016, held in Seville, Spain, in April 2016. The 63 full papers published in this volume were carefully reviewed and selected from 150 submissions. They are organized in topical sections on data mining and knowledge discovery; time series; bio-inspired models and evolutionary computation; learning algorithms; video and image; classification and cluster analysis; applications; bioinformatics; and hybrid intelligent systems for data mining and applications.

This book provides new approaches to forecast time series, based on data mining techniques. It explores several clustering algorithms and proposes methods to exploit their strengths when dealing with temporal data. This work proposes thus a brand new philosophy to forecast any kind of time series, as all introduced methodologies claim to be general- purpose. In fact, more than one hundred real-world time series have been analyzed with great accuracy.