Bücher der Reihe Studies in Computational Intelligence

This book is a collection of several contributions which show the state of the art in specific areas of Computational Intelligence.

This book covers the conventional and most recent theories and applications in the area of evolutionary algorithms, swarm intelligence, and meta-heuristics. All in all, the book offers a tutorial on how to design, adapt, and evaluate evolutionary algorithms.

This book is a tribute to Professor Jacek Zurada, who is best known for his contributions to computational intelligence and knowledge-based neurocomputing. It is dedicated to Professor Jacek Zurada, Full Professor at the Computational Intelligence Laboratory, Department of Electrical and Computer Engineering, J.B. Speed School of Engineering, University of Louisville, Kentucky, USA, as a token of appreciation for his scientific and scholarly achievements, and for his longstanding service to many communities, notably the computational intelligence community, in particular neural networks, machine learning, data analyses and data mining, but also the fuzzy logic and evolutionary computation communities, to name but a few.At the same time, the book recognizes and honors Professor Zurada's dedication and service to many scientific, scholarly and professional societies, especially the IEEE (Institute of Electrical and Electronics Engineers), the world's largest professional technical professional organization dedicated to advancing science and technology in a broad spectrum of areas and fields.The volume is divided into five major parts, the first of which addresses theoretic, algorithmic and implementation problems related to the intelligent use of data in the sense of how to derive practically useful information and knowledge from data. In turn, Part 2 is devoted to various aspects of neural networks and connectionist systems. Part 3 deals with essential tools and techniques for intelligent technologies in systems modeling and Part 4 focuses on intelligent technologies in decision-making, optimization and control, while Part 5 explores the applications of intelligent technologies.

This book addresses new challenges and emerging ideas in Distributed Information Filtering and Retrieval. It gathers extended papers presented at DART 2013 (the 7th International Workshop on Information Filtering and Retrieval), held on December 6, 2013 in Turin, Italy, and co-hosted with the XIII International Conference of the Italian Association for Artificial Intelligence. The main focus of DART was to discuss and compare suitable novel solutions based on intelligent techniques and applied to real-world contexts. The papers presented here offer a comprehensive review of related work and state-of-the-art techniques. The authors - a mix of respected practitioners and researchers - share their findings on a range of topics, including data leak protection on text comparison, natural language processing, ambient intelligence, information retrieval and web portals, and knowledge management. All contributions were carefully reviewed by experts in the respective area, who also provided useful suggestions to improve the book's overall quality.

This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students and practitioners a unique update on the latest advances in theory and a multitude of applications.

This book gathers the outcomes of several scientific events that were organized and conducted by the Institute of Scientific Communications (Volgograd, Russia) and the leading universities of the Volgograd region. The contributing authors include more than 700 scholars from various cities and regions of Russia. 124 works were selected out of 3,000 papers on the preconditions of formation, transformation, and legal provision of social institutes, topics that are in high demand in connection with a core aspect of digital modernization - the Internet of Things. The book is intended for a broad target audience, including scholars of various generations and various disciplines. These include young researchers (undergraduates and postgraduates) and recognized scholars (professors and lecturers) who study the socio-economic and legal consequences of the emergence and dissemination of digital technologies, including the Internet of Things. In addition, the book will benefit all those who are interested in the development of the information society, information and telecommunication, and digital technologies. The content is divided into three logical parts, the first of which is devoted to the essence of the process of institutionalization and legal regulation of the information society. In the second part, the digital economy is analyzed in view of the spheres of the national economy. In the third, the authors study the peculiarities of state and corporate regulation, infrastructural provision and support for the security of entrepreneurship, which are currently developing on the basis of the Internet of Things.

This book highlights recent research on interval methods for solving nonlinear constraint satisfaction, optimization and similar problems. Further, it presents a comprehensive survey of applications in various branches of robotics, artificial intelligence systems, economics, control theory, dynamical systems theory, and others.

This book examines theoretical and practical aspects of emerging technologies in e-service and artificial intelligence from an academic and professional viewpoint. To do so, it focuses on three major areas: the development of novel user support systems; development of smart mobility; and emerging technologies in Artificial Intelligence (AI). With regard to the development of novel user support systems, Chapter 1 introduces alternative ingredients recommendation using data on co-occurrence relation and ingredients categories to support cooking, while Chapter 2 introduces a study on location information inference using data acquired by low-energy Bluetooth devices. Turning to the development of smart mobility, Chapter 3 highlights a sustainable information infrastructure project for smart mobility systems. In addition, Chapter 4 presents a lifecycle-oriented development process to improve requirements and design in terms of uncertainties to provide sustainable information architectures for smart mobility.In the book's third and last part - emerging technologies in AI - Chapter 5 presents a summarization task for sports events on Twitter, focusing on an abstractive approach based on sub-events during the sports event. Chapter 6 discusses the generation of headlines using a recurrent neural network based on a machine translation approach. Lastly, Chapter 7 explores customer behavior analysis using enthusiasm analysis, an approach that estimates customers' activation levels. The book gathers a selection of the highest-quality papers presented at the 4th International Congress on Advanced Applied Informatics, held on July 12-16, 2015 in Okayama, Japan. Given the breadth of its coverage, it offers a valuable resource for practitioners, researchers and students alike.

This book gathers the peer-reviewed papers presented at the seventh edition of the international workshop "Service Orientation in Holonic and Multi-Agent Manufacturing - SOHOMA'17", held on October 19-20, 2017 and organized by the University of Nantes, France in collaboration with the CIMR Research Centre in Computer Integrated Manufacturing and Robotics at the University Politehnica of Bucharest, Romania, the LAMIH Laboratory of Industrial and Human Automation Control, Mechanical Engineering and Computer Science at the University of Valenciennes and Hainaut-Cambrésis, France and the CRAN Research Centre for Automatic Control, Nancy at the University of Lorraine, France. The main objective of SOHOMA'17 was to foster innovation in smart and sustainable manufacturing and logistics systems and in this context to promote concepts, methods and solutions addressing trends in service orientation of agent-based control technologies with distributed intelligence. The book is organized in eight parts, each with a number of chapters describing research in current domains of the digital transformation in manufacturing and trends in future service and computing oriented manufacturing control: Part 1: Advanced Manufacturing Control, Part 2: Big Data Management, Part 3: Cyber-Physical Production Systems, Part 4: Cloud- and Cyber-Physical Systems for Smart and Sustainable Manufacturing, Part 5: Simulation for Physical Internet and Intelligent & Sustainable Logistics Systems, Part 6: Formal Methods and Advanced Scheduling for Future Industrial Systems, Part 7: Applications and Demonstrators, Part 8: Production and Logistic Control Systems. The contributions focus on how the digital transformation, such as the one advocated by "Industry 4.0" or "Industry of the future" concepts, can improve the maintainability and the sustainability of manufacturing processes, products, and logistics. Digital transformation relates to the interaction between the physical and informational worlds and is realized by virtualization of products, processes and resources managed as services.

Pawlak. The proposed classifiers are applied and tested in two configurations: The first is an iterative mode in which a single classification system requests completion of the input data until an unequivocal decision (classification) is obtained.

This edited book presents scientific results of the 3nd International Conference on Applied Computing and Information Technology (ACIT 2015) which was held on July 12-16, 2015 in Okayama, Japan.

It is therefore necessary to come up with new techniques for processing the corresponding uncertainty that go beyond the traditional probabilistic techniques.This book focuses on such techniques, their economic applications and the remaining challenges, presenting both related theoretical developments and their practical applications.

The 22 chapters have been selected from the 168 papers published in the proceedings of the SAI Intelligent Systems Conference 2016 (IntelliSys 2016), which received highly positive feedback in peer reviews.

Foundations of Computational Intelligence Volume 1: Learning and Approximation: Theoretical Foundations and Applications Learning methods and approximation algorithms are fundamental tools that deal with computationally hard problems and problems in which the input is gradually disclosed over time.

Many decades have been devoted to creating and refining methods and tools for computational intelligence such as Artificial Neural Networks, Evolutionary Computation, Fuzzy Logic, Computational Swarm Intelligence and Artificial Immune Systems.

This is the fourth volume of the successful series Robot Operating Systems: The Complete Reference, providing a comprehensive overview of robot operating systems (ROS), which is currently the main development framework for robotics applications, as well as the latest trends and contributed systems.

This book explores the main concepts, algorithms, and techniques of Machine Learning and data mining for aerospace technology. Satellites are the 'eagle eyes' that allow us to view massive areas of the Earth simultaneously, and can gather more data, more quickly, than tools on the ground. Consequently, the development of intelligent health monitoring systems for artificial satellites - which can determine satellites' current status and predict their failure based on telemetry data - is one of the most important current issues in aerospace engineering.This book is divided into three parts, the first of which discusses central problems in the health monitoring of artificial satellites, including tensor-based anomaly detection for satellite telemetry data and machine learning in satellite monitoring, as well as the design, implementation, and validation of satellite simulators. The second part addresses telemetry data analytics and mining problems, while the last part focuses on security issues in telemetry data.

This book focuses on structural changes and economic modeling. It presents papers describing how to model structural changes, as well as those introducing improvements to the existing before-structural-changes models, making it easier to later on combine these models with techniques describing structural changes.

This book combines computational intelligence and mathematics to solve theoretical and real-world problems. The real challenges of engineering and other applied sciences, e.g. economics and management, the social sciences, etc., and even everyday life, are increasingly raising complex problems - both in the usual sense, but also in the mathematical and theoretical computer science sense, which is referred to as intractability. Finding exact solutions to the latest problems in mathematics is impossible, and it has been also shown that no further technical advance will ever make it possible to find general and exact solutions to such complex problems. Rather, the goal is to find solutions that are "good enough" or "acceptably accurate," including models and corresponding algorithms, which is most often achieved by combining traditional mathematical techniques and computational intelligence tools, such as fuzzy systems, evolutionary and memetic algorithms, and artificial neural networks.Consequently, international funding programs, such as the European Commission's current framework program for research and innovation (Horizon 2020), and the preliminary research team building COST Actions, are devoted to developing new instruments for tackling the challenges that we face in the current technological age. And it goes without saying that research topics concerning the interactions between computational intelligence and traditional mathematics play a key role in overcoming the obstacles associated with the intractability of complex problems. In this book, mathematicians, engineers, and other scientists highlight novel methodological results connecting these two main research areas, and focusing on solving real-life problems.

This book includes extended versions of selected works presented at the 52nd Annual Convention of Computer Society of India (CSI 2017), held at Science City, Kolkata on 19-21 January 2018.

This book highlights novel research in Knowledge Discovery and Management (KDM), gathering the extended, peer-reviewed versions of outstanding papers presented at the annual conferences EGC'2017 & EGC'2018.

This book presents the state of the art in designing high-performance algorithms that combine simulation and optimization in order to solve complex optimization problems in science and industry, problems that involve time-consuming simulations and expensive multi-objective function evaluations.

This book presents revised and extended versions of the best papers presented at the 9th International Joint Conference on Computational Intelligence (IJCCI 2017), held in Funchal, Madeira, from 1 to 3 November 2017.

This book gathers the outcomes of the 18th IEEE/ACIS International Conference on Computer and Information Science (ICIS 2019), which was held on June 12-14, 2019 in Beijing, China.

This book gathers the outcomes of the 7th International Conference on Applied Computing and Information Technology (ACIT 2019), which was held on May 29-31, 2019 in Honolulu, Hawaii.

The aim of the conference was to bring together researchers and scientists, businesspeople and entrepreneurs, teachers, engineers, computer users, and students to discuss the various fields of computer science and to share their experiences and exchange new ideas and information in a meaningful way.

This book presents research reports selected to indicate the state of the art in intelligent and database systems and to promote new research in this field. It includes 34 chapters based on original research presented as posters at the 11th Asian Conference on Intelligent Information and Database Systems (ACIIDS 2019), held in Yogyakarta, Indonesia on 8-11 April 2019.The increasing use of intelligent and database systems in various fields, such as industry, medicine and science places those two elements of computer science among the most important directions of research and application, which currently focuses on such key technologies as machine learning, cloud computing and processing of big data. It is estimated that further development of intelligent systems and the ability to gather, store and process enormous amounts of data will be needed to solve a number of crucial practical and theoretical problems.The book is divided into five parts: (a) Sensor Clouds and Internet of Things, (b) Machine Learning and Decision Support Systems, (c) Computer Vision Techniques and Applications, (d) Intelligent Systems in Biomedicine, and (e) Applications of Intelligent Information Systems.It is a valuable resource for researchers and practitioners interested in increasing the synergy between artificial intelligence and database technologies, as well as for graduate and Ph.D. students in computer science and related fields.

This book presents innovative and high-quality research regarding advanced decision support systems (DSSs). The first part covers decision support systems for industry, while the second part presents case studies related to clinical emergency management and pollution control.

This book explores new alternative metaheuristic developments that have proved to be effective in their application to several complex problems.

This edited book presents the scientific outcomes of the 17th International Conference on Software Engineering, Artificial Intelligence Research, Management and Applications (SERA 2019) held on May 29-31, 2019 in Honolulu, Hawaii.