Metaheuristic optimization has become a prime alternative for solving complex optimization problems in several areas. Hence, practitioners and researchers have been paying extensive attention to those metaheuristic algorithms that are mainly based on natural phenomena. However, when those algorithms are implemented, there are not enough books that deal with theoretical and experimental problems in a friendly manner so this book presents a novel structure that includes a complete description of the most important metaheuristic optimization algorithms as well as a new proposal of a new metaheuristic optimization named earthquake optimization. This book also has several practical exercises and a toolbox for MATLAB® and a toolkit for LabVIEW are integrated as complementary material for this book. These toolkits allow readers to move from a simulation environment to an experimentation one very fast. This book is suitable for researchers, students, and professionals in several areas, such as economics, architecture, computer science, electrical engineering, and control systems. The unique features of this book are as follows: Developed for researchers, undergraduate and graduate students, and practitioners A friendly description of the main metaheuristic optimization algorithms Theoretical and practical optimization examples A new earthquake optimization algorithm Updated state-of-the-art and research optimization projects The authors are multidisciplinary/interdisciplinary lecturers and researchers who have written a structure-friendly learning methodology to understand each metaheuristic optimization algorithm presented in this book.

Metaheuristic optimization has become a prime alternative for solving complex optimization problems in several areas. Hence, practitioners and researchers have been paying extensive attention to those metaheuristic algorithms that are mainly based on natural phenomena. However, when those algorithms are implemented, there are not enough books that deal with theoretical and experimental problems in a friendly manner so this book presents a novel structure that includes a complete description of the most important metaheuristic optimization algorithms as well as a new proposal of a new metaheuristic optimization named earthquake optimization. This book also has several practical exercises and a toolbox for MATLAB® and a toolkit for LabVIEW are integrated as complementary material for this book. These toolkits allow readers to move from a simulation environment to an experimentation one very fast. This book is suitable for researchers, students, and professionals in several areas, such as economics, architecture, computer science, electrical engineering, and control systems. The unique features of this book are as follows: Developed for researchers, undergraduate and graduate students, and practitioners A friendly description of the main metaheuristic optimization algorithms Theoretical and practical optimization examples A new earthquake optimization algorithm Updated state-of-the-art and research optimization projects The authors are multidisciplinary/interdisciplinary lecturers and researchers who have written a structure-friendly learning methodology to understand each metaheuristic optimization algorithm presented in this book.

This book is a collection of the most recent approaches that combine metaheuristics and machine learning. Some of the methods considered in this book are evolutionary, swarm, machine learning, and deep learning. The chapters were classified based on the content; then, the sections are thematic. Different applications and implementations are included; in this sense, the book provides theory and practical content with novel machine learning and metaheuristic algorithms. The chapters were compiled using a scientific perspective. Accordingly, the book is primarily intended for undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics and is useful in courses on Artificial Intelligence, Advanced Machine Learning, among others. Likewise, the book is useful for research from the evolutionary computation, artificial intelligence, and image processing communities.

This is an open access book.The First International Conference on Innovation in information technology and business (ICIITB) will be taking place in Muscat, Oman, on November 9th and 10th, 2022. The Conference will be carried out in a hybrid format, allowing world-scattered academicians, researchers, and industry professionals to participate in this unique Conference for Oman and the GCC region. The participants of the Conference will get an opportunity to contribute to the contemporary implementation of cutting-edge research and development in the area of artificial intelligence, data science, machine learning, and the IoT in the business environment. The participants will get a first-of-a-kind networking and knowledge sharing opportunity to be a part of an event in Oman, that will gather recognized researchers from the GCC, Europe, the USA, and other parts of the World. Select research papers will also be published in a Springer-published Conference proceedings.

This book presents a detailed description, analysis, comparison of the latest research and developments in photovoltaic energy. Discussing everything from semiconductors to system integration, and applying various advanced technologies to stand alone and electric utility interfaced in normal and abnormal operating conditions of PV systems, this book provides a thorough introduction to the topic. This book brings together research from around the world, covering the use of technologies such as embedded systems, the Internet of things and blockchain technologies for PV systems for different applications including controllers, solar trackers and cooling systems. The book is of interest to electronic and mechanical engineers, researchers and students in the field of photovoltaics.

Widely used across industrial and manufacturing automation, Programmable Logic Controllers (PLCs) perform a broad range of electromechanical tasks with multiple input and output arrangements, designed specifically to cope in severe environmental conditions such as automotive and chemical plants. Programmable Logic Controllers: A Practical Approach using CoDeSys is a hands-on guide to rapidly gain proficiency in the development and operation of PLCs based on the IEC 61131-3 standard. Using the freely-available* software tool CoDeSys, which is widely used in industrial design automation projects, the author takes a highly practical approach to PLC design using real-world examples. The design tool, CoDeSys, also features a built in simulator/soft PLC enabling the reader to undertake exercises and test the examples. Key features: Introduces to programming techniques using IEC 61131-3 guidelines in the five PLC-recognised programming languages. Focuses on a methodical approach to programming, based on Boolean algebra, flowcharts, sequence diagrams and state-diagrams. Contains a useful methodology to solve problems, develop a structured code and document the programming code. Covers I/O like typical sensors, signals, signal formats, noise and cabling. Features Power Point slides covering all topics, example programs and solutions to end-of-chapter exercises via companion website. No prior knowledge of programming PLCs is assumed making this text ideally suited to electronics engineering students pursuing a career in electronic design automation. Experienced PLC users in all fields of manufacturing will discover new possibilities and gain useful tips for more efficient and structured programming. * Register at www.codesys.com www.wiley.com/go/hanssen/logiccontrollers

Introduction to Pattern Recognition: A Matlab Approach is an accompanying manual to Theodoridis/Koutroumbas' Pattern Recognition. It includes Matlab code of the most common methods and algorithms in the book, together with a descriptive summary and solved examples, and including real-life data sets in imaging and audio recognition. This text is designed for electronic engineering, computer science, computer engineering, biomedical engineering and applied mathematics students taking graduate courses on pattern recognition and machine learning as well as R&D engineers and university researchers in image and signal processing/analyisis, and computer vision. - Matlab code and descriptive summary of the most common methods and algorithms in Theodoridis/Koutroumbas, Pattern Recognition, Fourth Edition - Solved examples in Matlab, including real-life data sets in imaging and audio recognition - Available separately or at a special package price with the main text (ISBN for package: 978-0-12-374491-3)