This book is a guide to the combination of the Internet of Things (IoT) and the Semantic Web, covering a variety of tools, technologies and applications that serve the myriad needs of the researchers in this field. It provides a multi dimensional view of the concepts, tools, techniques and issues that are involved in the development of semantics for the Web of Things.The various aspects studied in this book include Multi-Model Multi-Platform (SHM3P) databases for the IoT, clusterin...

Machine learning and optimization techniques are revolutionizing our world. Other types of information technology have not progressed as rapidly in recent years, in terms of real impact. The aim of this book is to present some of the innovative techniques in the field of optimization and machine learning, and to demonstrate how to apply them in the fields of engineering.Optimization and Machine Learning presents modern advances in the selection, configuration and engineeri...

This book provides a comprehensive compilation of the latest research and advancements presented at the First International Symposium on Biomechatronics and Robotics in Healthcare (BioMRH 2025). The proceedings cover key topics such as the integration of robotic systems in healthcare, biomechatronics for rehabilitation, smart biomaterials, AI and machine learning in medical diagnostics and treatment, human-machine interfaces, and ethical challenges in healthcare robotics. By exploring how ...

This book describes the optimization methods most commonly encountered in signal and image processing: artificial evolution and Parisian approach; wavelets and fractals; information criteria; training and quadratic programming; Bayesian formalism; probabilistic modeling; Markovian approach; hidden Markov models; and metaheuristics (genetic algorithms, ant colony algorithms, cross-entropy, particle swarm optimization, estimation of distribution algorithms, and artificial immune systems).

This book describes the potentialities of metaheuristics for solving production scheduling problems and the relationship between these two fields.For the past several years, there has been an increasing interest in using metaheuristic methods to solve scheduling problems. The main reasons for this are that such problems are generally hard to solve to optimality, as well as the fact that metaheuristics provide very good solutions in a reasonable time. The first part...

Computational Intelligence for Medical Internet of Things (MIoT) Applications: Machine Intelligence Applications for IoT in Healthcare explores machine intelligence techniques necessary for effective MIoT research and practice, taking a practical approach for practitioners and students entering the field. This book investigates advanced concepts and applications in the MIoT field, guiding readers through emerging developments and future trends. A wide range of international authors guide r...

Graph partitioning is a theoretical subject with applications in many areas, principally: numerical analysis, programs mapping onto parallel architectures, image segmentation, VLSI design. During the last 40 years, the literature has strongly increased and big improvements have been made.This book brings together the knowledge accumulated during many years to extract both theoretical foundations of graph partitioning and its main applications.

This book provides a comprehensive compilation of the latest research and advancements presented at the First International Symposium on Biomechatronics and Robotics in Healthcare (BioMRH 2025). The proceedings cover key topics such as the integration of robotic systems in healthcare, biomechatronics for rehabilitation, smart biomaterials, AI and machine learning in medical diagnostics and treatment, human-machine interfaces, and ethical challenges in healthcare robotics. By exploring how ...

This book constitutes the thoroughly refereed post-conference proceedings of the Second International Conference on Swarm Intelligence Based Optimization, ICSIBO 2016, held in Mulhouse, France, in June 2016. The 9 full papers presented were carefully reviewed and selected from 20 submissions. They are centered around the following topics: theoretical advances of swarm intelligence metaheuristics; combinatorial discrete, binary, constrained, multi-objective, multi-modal, dynamic, noisy, and...

In today’s world, the concept of a circular economy has emerged as a vital solution to address pressing environmental concerns and foster sustainable development. At its core, the circular economy aims to minimize waste generation by keeping resources in use for as long as possible, thereby reducing the strain on natural ecosystems and promoting resource efficiency.Operations research and data science play a crucial role in implementing circular economy principles by bridging the g...

Using metaheuristics to enhance machine learning techniques has become trendy and has achieved major successes in both supervised (classification and regression) and unsupervised (clustering and rule mining) problems. Furthermore, automatically generating programs via metaheuristics, as a form of evolutionary computation and swarm intelligence, has now gained widespread popularity. This book investigates different ways of integrating metaheuristics into machine learning techniques, from bo...

The escalating tide of waste and environmental threats demands a paradigm shift in how we produce and consume waste. The circular economy emerges as a beacon of hope, offering a transformative approach that breaks free from the traditional "take make dispose" model. This innovative system prioritizes sustainable practices throughout a product's lifecycle, promoting reuse, recycling, and regeneration. By fostering the development of robust and closed loop supply chains, the circular economy...