The development of nature-inspired computational techniques has enhanced problem solving in dynamic and uncertain environments. By implementing effective computing strategies, this ensures adaptable, self-organizing, and decentralized behavioral techniques. Recent Developments in Intelligent Nature-Inspired Computing is an authoritative reference source for the latest scholarly material on natural computation methods and applications in diverse fields. Highlighting multidisciplinary studies on swarm intelligence, global optimization, and group technology, this publication is an ideal reference source for professionals, researchers, scholars, and engineers interested in the latest developments in computer science methodologies.

This book offers a collection of high-quality, peer-reviewed research papers presented at the International Conference on Intelligent Computing, Communication and Devices (ICCD 2017), discussing all dimensions of intelligent sciences – intelligent computing, intelligent communication, and intelligent devices. Intelligent computing addresses areas such as intelligent and distributed computing, intelligent grid and cloud computing, internet of things, soft computing and engineering applications, data mining and knowledge discovery, semantic and web technology, hybrid systems, agent computing, bioinformatics, and recommendation systems. Intelligent communication is concerned with communication and network technologies, such as mobile broadband and all optical networks that are the key to groundbreaking inventions of intelligent communication technologies. It includes communication hardware, software and networked intelligence, mobile technologies, machine-to-machine communication networks, speech and natural language processing, routing techniques and network analytics, wireless ad hoc and sensor networks, communications and information security, signal, image and video processing, network management, and traffic engineering. Lastly, intelligent devices are any equipment, instruments, or machines that have their own computing capability. As computing technology becomes more advanced and less expensive, it can be incorporated an increasing number of devices of all kinds. This area covers such as embedded systems, radiofrequency identification (RFID), radiofrequency microelectromechanical system (RF MEMS), very-large-scale integration (VLSI) design and electronic devices, analog and mixed-signal integrated circuit (IC) design and testing, microelectromechanical system (MEMS) and microsystems, solar cells and photonics, nanodevices, single electron and spintronics devices, space electronics, and intelligent robotics.

Nature-inspired computation and swarm intelligence have become popular and effective tools for solving problems in optimization, computational intelligence, soft computing and data science. Recently, the literature in the field has expanded rapidly, with new algorithms and applications emerging. Nature-Inspired Computation and Swarm Intelligence: Algorithms, Theory and Applications is a timely reference giving a comprehensive review of relevant state-of-the-art developments in algorithms, theory and applications of nature-inspired algorithms and swarm intelligence. It reviews and documents the new developments, focusing on nature-inspired algorithms and their theoretical analysis, as well as providing a guide to their implementation. The book includes case studies of diverse real-world applications, balancing explanation of the theory with practical implementation. Nature-Inspired Computation and Swarm Intelligence: Algorithms, Theory and Applications is suitable for researchers and graduate students in computer science, engineering, data science, and management science, who want a comprehensive review of algorithms, theory and implementation within the fields of nature inspired computation and swarm intelligence. - Introduces nature-inspired algorithms and their fundamentals, including: particle swarm optimization, bat algorithm, cuckoo search, firefly algorithm, flower pollination algorithm, differential evolution and genetic algorithms as well as multi-objective optimization algorithms and others - Provides a theoretical foundation and analyses of algorithms, including: statistical theory and Markov chain theory on the convergence and stability of algorithms, dynamical system theory, benchmarking of optimization, no-free-lunch theorems, and a generalized mathematical framework - Includes a diversity of case studies of real-world applications: feature selection, clustering and classification, tuning of restricted Boltzmann machines, travelling salesman problem, classification of white blood cells, music generation by artificial intelligence, swarm robots, neural networks, engineering designs and others

Mankind’s dependence on artificial intelligence and robotics is increasing rapidly as technology becomes more advanced. Finding a way to seamlessly intertwine these two worlds will help boost productivity in society and aid in a variety of ways in modern civilization. Androids, Cyborgs, and Robots in Contemporary Culture and Society is an essential scholarly resource that delves into the current issues, methodologies, and trends relating to advanced robotic technology in the modern world. Featuring relevant topics that include STEM technologies, brain-controlled androids, biped robots, and media perception, this publication is ideal for engineers, academicians, students, and researchers that would like to stay current with the latest developments in the world of evolving robotics.

World Congress on Nature and Biologically Inspired Computing (NaBIC) is organized to discuss the state-of-the-art as well as to address various issues with respect to Nurturing Intelligent Computing Towards Advancement of Machine Intelligence. This Volume contains the papers presented in the Seventh World Congress (NaBIC’15) held in Pietermaritzburg, South Africa during December 01-03, 2015. The 39 papers presented in this Volume were carefully reviewed and selected. The Volume would be a valuable reference to researchers, students and practitioners in the computational intelligence field.

Continuous improvements in technological applications have allowed more opportunities to develop automated systems. This not only leads to higher success in smart data analysis, but it increases the overall probability of technological progression. The Handbook of Research on Machine Learning Innovations and Trends is a key resource on the latest advances and research regarding the vast range of advanced systems and applications involved in machine intelligence. Highlighting multidisciplinary studies on decision theory, intelligent search, and multi-agent systems, this publication is an ideal reference source for professionals and researchers working in the field of machine learning and its applications.

The objective of this book is to contribute to the development of the intelligent information and database systems with the essentials of current knowledge, experience and know-how. The book contains a selection of 40 chapters based on original research presented as posters during the 8th Asian Conference on Intelligent Information and Database Systems (ACIIDS 2016) held on 14–16 March 2016 in Da Nang, Vietnam. The papers to some extent reflect the achievements of scientific teams from 17 countries in five continents. The volume is divided into six parts: (a) Computational Intelligence in Data Mining and Machine Learning, (b) Ontologies, Social Networks and Recommendation Systems, (c) Web Services, Cloud Computing, Security and Intelligent Internet Systems, (d) Knowledge Management and Language Processing, (e) Image, Video, Motion Analysis and Recognition, and (f) Advanced Computing Applications and Technologies. The book is an excellent resource for researchers, those working in artificial intelligence, multimedia, networks and big data technologies, as well as for students interested in computer science and other related fields.

This volume comprises the select proceedings of the annual convention of the Computer Society of India. Divided into 10 topical volumes, the proceedings present papers on state-of-the-art research, surveys, and succinct reviews. The volumes cover diverse topics ranging from communications networks to big data analytics, and from system architecture to cyber security. This volume focuses on Nature Inspired Computing. The contents of this book will be useful to researchers and students alike.

This book presents high-quality papers from an international forum for research on computational approaches to learning. It includes current research and findings from various research labs, universities and institutions that may lead to development of marketable products. It also provides solid support for these findings in the form of empirical studies, theoretical analysis, or comparison to psychological phenomena. Further, it features work that shows how to apply learning methods to solve important application problems as well as how machine learning research is conducted. The book is divided into two main parts: Machine Learning Techniques, which covers machine learning-related research and findings; and, Data Analytics, which introduces recent developments in this domain. Additionally, the book includes work on data analytics using machine learning techniques.

This book gathers selected papers presented at the Third International Conference on Mechatronics and Intelligent Robotics (ICMIR 2019), held in Kunming, China, on May 25–26, 2019. The proceedings cover new findings in the following areas of research: mechatronics, intelligent mechatronics, robotics and biomimetics; novel and unconventional mechatronic systems; modeling and control of mechatronic systems; elements, structures and mechanisms of micro- and nano-systems; sensors, wireless sensor networks and multi-sensor data fusion; biomedical and rehabilitation engineering, prosthetics and artificial organs; artificial intelligence (AI), neural networks and fuzzy logic in mechatronics and robotics; industrial automation, process control and networked control systems; telerobotics and human–computer interaction; human–robot interaction; robotics and artificial intelligence; bio-inspired robotics; control algorithms and control systems; design theories and principles; evolutional robotics; field robotics; force sensors, accelerometers and other measuring devices; healthcare robotics; kinematics and dynamics analysis; manufacturing robotics; mathematical and computational methodologies in robotics; medical robotics; parallel robots and manipulators; robotic cognition and emotion; robotic perception and decisions; sensor integration, fusion and perception; and social robotics.