A critical part of ensuring that systems are advancing alongside technology without complications is problem solving. Practical applications of problem-solving theories can model conflict and cooperation and aid in creating solutions to real-world problems. Soft-Computing-Based Nonlinear Control Systems Design is a critical scholarly publication that examines the practical applications of control theory and its applications in problem solving to fields including economics, environmental management, and financial modelling. Featuring a wide range of topics, such as fuzzy logic, nature-inspired algorithms, and cloud computing, this book is geared toward academicians, researchers, and students seeking relevant research on control theory and its practical applications.

Soft computing and nature-inspired computing both play a significant role in developing a better understanding to machine learning. When studied together, they can offer new perspectives on the learning process of machines. The Handbook of Research on Soft Computing and Nature-Inspired Algorithms is an essential source for the latest scholarly research on applications of nature-inspired computing and soft computational systems. Featuring comprehensive coverage on a range of topics and perspectives such as swarm intelligence, speech recognition, and electromagnetic problem solving, this publication is ideally designed for students, researchers, scholars, professionals, and practitioners seeking current research on the advanced workings of intelligence in computing systems.

Soft computing techniques are emerging as an important tool in solving design, performance and optimisation problems in electromagnetics. Soft Computing in Electromagnetics offers detailed discussion on the application of soft computing concepts in the field of metamaterial antennas, radar absorbers, transmission line characterisation and optimised radar absorbing material (RAM) and introduces implementation of soft computing tools in a relatively new area of metamaterials. The soft computing methods are used to optimise fault detection, electromagnetic propagation and path loss detection. The development of two CAD packages for design of metamaterial split ring resonators (SRR) and path-loss prediction is discussed. The concepts are explained with the help of algorithms and the corresponding software codes. Numerical examples and MATLAB codes are provided throughout the text to facilitate understanding.

This book contains papers presented at the International Symposium on Elect- magnetic Fields in Mechatronics, Electrical and Electronic Engineering ISEF’07 which was held in Prague, the Czech Republic, from September 13 to 15, 2007. ISEF conferences have been organized since 1985 and from the very beginning it was a common initiative of Polish and other European researchers who have dealt with electromagnetic ?eld in electrical engineering. The conference travels through Europe and is organized in various academic centres. Relatively often, it was held in some Polish city as the initiative was on the part of Polish scientists. Now ISEF is much more international and successive events take place in different European academic centres renowned for electromagnetic research. This time it was Prague, famous for its beauty and historical background, as it is the place where many c- tures mingle. The venue of the conference was the historical building of Charles University, placed just in the centre of Prague. The Technical University of Prague, in turn, constituted the logistic centre of the conference. It is the tradition of the ISEF meetings that they try to tackle quite a vast area of computational and applied electromagnetics. Moreover, the ISEF symposia aim at combining theory and practice; therefore the majority of papers are deeply rooted in engineering problems, being simultaneously of a high theoretical level.

Soft computing, as opposed to conventional "hard" computing, tolerates imprecision and uncertainty, in a way very much similar to the human mind. Soft computing techniques include neural networks, evolutionary computation, fuzzy logic, and chaos. The recent years have witnessed tremendous success of these powerful methods in virtually all areas of science and technology, as evidenced by the large numbers of research results published in a variety of journals, conferences, as weil as many excellent books in this book series on Studies in Fuzziness and Soft Computing. This volume is dedicated to recent novel applications of soft computing in communications. The book is organized in four Parts, i.e., (1) neural networks, (2) evolutionary computation, (3) fuzzy logic and neurofuzzy systems, and (4) kernel methods. Artificial neural networks consist of simple processing elements called neurons, which are connected by weights that may be adjusted during learning. Part 1 of the book has seven chapters, demonstrating some of the capabilities of two major types of neural networks, i.e., multiplayer perceptron (MLP) neural networks and Hopfield-type neural networks.

Differential evolution has proven itself a very simple while very powerful stochastic global optimizer. It has been applied to solve problems in many scientific and engineering fields. This book focuses on applications of differential evolution in electromagnetics to showcase its achievement and capability in solving synthesis and design problems in electromagnetics.Topics covered in this book include:• A comprehensive up-to-date literature survey on differential evolution• A systematic description of differential evolution• A topical review on applications of differential evolution in electromagnetics• Five new application examplesThis book is ideal for electromagnetic researchers and people in differential evolution community. It is also a valuable reference book for researchers and students in the optimization or electrical and electronic engineering field. In addition, managers and engineers in relevant fields will find it a helpful introductory guide.

This book presents a novel methodology for the computation of RCS of metallic structures using a parallelized version of NEC in conjunction with a finite element preprocessor which has been strategically incorporated for simplifying geometry modelling catering to NEC guidelines. It includes a thorough overview of the theoretical background of NEC including all relevant aspects of formulation and modelling. The revised methodology including all the required steps and details is discussed elaborately along with case studies and validations. This book will serve as a valuable resource for students, researchers, scientists, and engineers working in the field of RCS predictions and measurements.

This book focuses on the role of soft-computing-based electromagnetic computational engines in design and optimization of a wide range of electromagnetic applications. In addition to the theoretical background of metamaterials and soft-computing techniques, the book discusses novel electromagnetic applications such as tensor analysis for invisibility cloaking, metamaterial structures for cloaking applications, broadband radar absorbers, and antennas. The book will prove to be a valuable resource for academics and professionals, as well as military researchers working in the area of metamaterials.

The book discusses the latest developments and outlines future trends in the fields of microelectronics, electromagnetics and telecommunication. It contains original research works presented at the International Conference on Microelectronics, Electromagnetics and Telecommunication (ICMEET 2018), organised by GVP College of Engineering (A), Andhra Pradesh, India. The respective papers were written by scientists, research scholars and practitioners from leading universities, engineering colleges and R&D institutes from all over the world, and share the latest breakthroughs in and promising solutions to the most important issues facing today’s society.

The high-speed capabilities and learning abilities of neural networks can be applied to quickly solving numerous complex optimization problems in electromagnetics, and this book shows you how. Even if you have no background in neural networks, this book helps you understand the basics of each main network architecture in use today, including its strengths and limitations. Moreover, it gives you the knowledge you need to identify situations when the use of neural networks is the best problem-solving option.