This unique book provides a comprehensive introduction to computational mathematics, which forms an essential part of contemporary numerical algorithms, scientific computing and optimization. It uses a theorem-free approach with just the right balance between mathematics and numerical algorithms. This edition covers all major topics in computational mathematics with a wide range of carefully selected numerical algorithms, ranging from the root-finding algorithm, numerical integration, numerical methods of partial differential equations, finite element methods, optimization algorithms, stochastic models, nonlinear curve-fitting to data modelling, bio-inspired algorithms and swarm intelligence. This book is especially suitable for both undergraduates and graduates in computational mathematics, numerical algorithms, scientific computing, mathematical programming, artificial intelligence and engineering optimization. Thus, it can be used as a textbook and/or reference book.

This unique book provides a comprehensive introduction to computational mathematics, which forms an essential part of contemporary numerical algorithms, scientific computing and optimization. It uses a theorem-free approach with just the right balance between mathematics and numerical algorithms. This edition covers all major topics in computational mathematics with a wide range of carefully selected numerical algorithms, ranging from the root-finding algorithm, numerical integration, numerical methods of partial differential equations, finite element methods, optimization algorithms, stochastic models, nonlinear curve-fitting to data modelling, bio-inspired algorithms and swarm intelligence. This book is especially suitable for both undergraduates and graduates in computational mathematics, numerical algorithms, scientific computing, mathematical programming, artificial intelligence and engineering optimization. Thus, it can be used as a textbook and/or reference book.

Computer-aided full-wave electromagnetic (EM) analysis has been used in microwave engineering for the past decade. Initially, its main application area was design verification. Today, EM-simulation-driven optimization and design closure become increasingly important due to the complexity of microwave structures and increasing demands for accuracy. In many situations, theoretical models of microwave structures can only be used to yield the initial designs that need to be further fine-tuned to meet given performance requirements. In addition, EM-based design is a must for a growing number of microwave devices such as ultra-wideband (UWB) antennas, dielectric resonator antennas and substrate-integrated circuits. For circuits like these, no design-ready theoretical models are available, so design improvement can only be obtained through geometry adjustments based on repetitive, time-consuming simulations. On the other hand, various interactions between microwave devices and their environment, such as feeding structures and housing, must be taken into account, and this is only possible through full-wave EM analysis.Electromagnetic simulations can be highly accurate, but they tend to be computationally expensive. Therefore, practical design optimization methods have to be computationally efficient, so that the number of CPU-intensive high-fidelity EM simulations is reduced as much as possible during the design process. For the same reasons, techniques for creating fast yet accurate models of microwave structures become crucially important.In this edited book, the authors strive to review the state-of-the-art simulation-driven microwave design optimization and modeling. A group of international experts specialized in various aspects of microwave computer-aided design summarize and review a wide range of the latest developments and real-world applications. Topics include conventional and surrogate-based design optimization techniques, methods exploiting adjoint sensitivity, simulation-based tuning, space mapping, and several modeling methodologies, such as artificial neural networks and kriging. Applications and case studies include microwave filters, antennas, substrate integrated structures and various active components and circuits. The book also contains a few introductory chapters highlighting the fundamentals of optimization and modeling, gradient-based and derivative-free algorithms, metaheuristics, and surrogate-based optimization techniques, as well as finite difference and finite element methods.

This unique book provides a comprehensive introduction to computational mathematics, which forms an essential part of modern numerical algorithms and scientific computing. It uses a theorem-free approach with just the right balance between mathematics and numerical algorithms. It covers all major topics in computational mathematics with a wide range of carefully selected numerical algorithms, ranging from the root-finding algorithms, numerical integration, numerical methods of partial differential equations, finite element methods, optimization algorithms, stochastic models, to nonlinear curve-fitting and swarm optimization. Especially suitable for undergraduates and graduates in computational mathematics, numerical algorithms, and scientific computing, it can be used as a textbook and/or reference book.

This book gravitates on the prominent theories and recent developments of swarm intelligence methods, and their application in both synthetic and real-world optimization problems. The special interest will be placed in those algorithmic variants where biological processes observed in nature have underpinned the core operators underlying their search mechanisms. In other words, the book centers its attention on swarm intelligence and nature-inspired methods for efficient optimization and problem solving. The content of this book unleashes a great opportunity for researchers, lecturers and practitioners interested in swarm intelligence, optimization problems and artificial intelligence.

This book gravitates on the prominent theories and recent developments of swarm intelligence methods, and their application in both synthetic and real-world optimization problems. The special interest will be placed in those algorithmic variants where biological processes observed in nature have underpinned the core operators underlying their search mechanisms. In other words, the book centers its attention on swarm intelligence and nature-inspired methods for efficient optimization and problem solving. The content of this book unleashes a great opportunity for researchers, lecturers and practitioners interested in swarm intelligence, optimization problems and artificial intelligence.

This book discusses all the major nature-inspired algorithms with a focus on their application in the context of solving navigation and routing problems. It also reviews the approximation methods and recent nature-inspired approaches for practical navigation, and compares these methods with traditional algorithms to validate the approach for the case studies discussed. Further, it examines the design of alternative solutions using nature-inspired techniques, and explores the challenges of navigation and routing problems and nature-inspired metaheuristic approaches.

This book gathers selected high-quality research papers presented at the Fifth International Congress on Information and Communication Technology, held at Brunel University, London, on February 20-21, 2020. It discusses emerging topics pertaining to information and communication technology (ICT) for managerial applications, e-governance, e-agriculture, e-education and computing technologies, the Internet of Things (IoT) and e-mining. Written by respected experts and researchers working on ICT, the book offers a valuable asset for young researchers involved in advanced studies.

This book gathers selected high-quality research papers presented at the Fifth International Congress on Information and Communication Technology, held at Brunel University, London, on February 20-21, 2020. It discusses emerging topics pertaining to information and communication technology (ICT) for managerial applications, e-governance, e-agriculture, e-education and computing technologies, the Internet of Things (IoT) and e-mining. Written by respected experts and researchers working on ICT, the book offers a valuable asset for young researchers involved in advanced studies.

This book reviews the latest developments in nature-inspired computation, with a focus on the cross-disciplinary applications in data mining and machine learning. Data mining, machine learning and nature-inspired computation are current hot research topics due to their importance in both theory and practical applications. Adopting an application-focused approach, each chapter introduces a specific topic, with detailed descriptions of relevant algorithms, extensive literature reviews and implementation details. Covering topics such as nature-inspired algorithms, swarm intelligence, classification, clustering, feature selection, cybersecurity, learning algorithms over cloud, extreme learning machines, object categorization, particle swarm optimization, flower pollination and firefly algorithms, and neural networks, it also presents case studies and applications, including classifications of crisis-related tweets, extraction of named entities in the Tamil language, performance-based prediction of diseases, and healthcare services. This book is both a valuable a reference resource and a practical guide for students, researchers and professionals in computer science, data and management sciences, artificial intelligence and machine learning.

This book gathers selected high-quality papers presented at the International Conference on Machine Learning and Computational Intelligence (ICMLCI-2019), jointly organized by Kunming University of Science and Technology and the Interscience Research Network, Bhubaneswar, India, from April 6 to 7, 2019. Addressing virtually all aspects of intelligent systems, soft computing and machine learning, the topics covered include: prediction; data mining; information retrieval; game playing; robotics; learning methods; pattern visualization; automated knowledge acquisition; fuzzy, stochastic and probabilistic computing; neural computing; big data; social networks and applications of soft computing in various areas.

This book discusses all the major nature-inspired algorithms with a focus on their application in the context of solving navigation and routing problems. It also reviews the approximation methods and recent nature-inspired approaches for practical navigation, and compares these methods with traditional algorithms to validate the approach for the case studies discussed. Further, it examines the design of alternative solutions using nature-inspired techniques, and explores the challenges of navigation and routing problems and nature-inspired metaheuristic approaches.

The second volume of this book includes selected high-quality research papers presented at the Fourth International Congress on Information and Communication Technology, which was held at Brunel University, London, on February 27-28, 2019. It discusses emerging topics pertaining to information and communication technology (ICT) for managerial applications, e-governance, e-agriculture, e-education and computing technologies, the Internet of Things (IoT), and e-mining. Written by respected experts and researchers actively working in ICT, the book offers a valuable resource, especially for researchers who are newcomers to the field.

This book gathers selected high-quality research papers presented at the Fourth International Congress on Information and Communication Technology, held at Brunel University, London, on February 27-28, 2019. It discusses emerging topics pertaining to information and communication technology (ICT) for managerial applications, e-governance, e-agriculture, e-education and computing technologies, the Internet of things (IoT), and e-mining. Written by respected experts and researchers working on ICT, the book offers a valuable asset for young researchers involved in advanced studies.

This book reviews the latest developments in nature-inspired computation, with a focus on the cross-disciplinary applications in data mining and machine learning. Data mining, machine learning and nature-inspired computation are current hot research topics due to their importance in both theory and practical applications. Adopting an application-focused approach, each chapter introduces a specific topic, with detailed descriptions of relevant algorithms, extensive literature reviews and implementation details. Covering topics such as nature-inspired algorithms, swarm intelligence, classification, clustering, feature selection, cybersecurity, learning algorithms over cloud, extreme learning machines, object categorization, particle swarm optimization, flower pollination and firefly algorithms, and neural networks, it also presents case studies and applications, including classifications of crisis-related tweets, extraction of named entities in the Tamil language, performance-based prediction of diseases, and healthcare services. This book is both a valuable a reference resource and a practical guide for students, researchers and professionals in computer science, data and management sciences, artificial intelligence and machine learning.

This timely book deals with a current topic, i.e. the applications of metaheuristic algorithms, with a primary focus on optimization problems in civil engineering. The first chapter offers a concise overview of different kinds of metaheuristic algorithms, explaining their advantages in solving complex engineering problems that cannot be effectively tackled by traditional methods, and citing the most important works for further reading. The remaining chapters report on advanced studies on the applications of certain metaheuristic algorithms to specific engineering problems. Genetic algorithm, bat algorithm, cuckoo search, harmony search and simulated annealing are just some of the methods presented and discussed step by step in real-application contexts, in which they are often used in combination with each other. Thanks to its synthetic yet meticulous and practice-oriented approach, the book is a perfect guide for graduate students, researchers and professionals willing to applying metaheuristic algorithms in civil engineering and other related engineering fields, such as mechanical, transport and geotechnical engineering. It is also a valuable aid for both lectures and advanced engineering students.

This book gathers a wealth of research contributions on recent advances in intelligent and distributed computing, and which present both architectural and algorithmic findings in these fields. A major focus is placed on new techniques and applications for evolutionary computation, swarm intelligence, multi-agent systems, multi-criteria optimization and Deep/Shallow machine learning models, all of which are approached as technological drivers to enable autonomous reasoning and decision-making in complex distributed environments. Part of the book is also devoted to new scheduling and resource allocation methods for distributed computing systems. The book represents the peer-reviewed proceedings of the 12th International Symposium on Intelligent Distributed Computing (IDC 2018), which was held in Bilbao, Spain, from October 15 to 17, 2018.

The book gathers a collection of high-quality peer-reviewed research papers presented at the International Conference on Information System Design and Intelligent Applications (INDIA 2018), which was held at the Universite des Mascareignes, Mauritius from July 19 to 21, 2018. It covers a wide range of topics in computer science and information technology, from image processing, database applications and data mining, to grid and cloud computing, bioinformatics and many more. The intelligent tools discussed, e.g. swarm intelligence, artificial intelligence, evolutionary algorithms, and bio-inspired algorithms, are currently being applied to solve challenging problems in various domains.

The book gathers a collection of high-quality peer-reviewed research papers presented at the International Conference on Information System Design and Intelligent Applications (INDIA 2018), which was held at the Universite des Mascareignes, Mauritius from July 19 to 21, 2018. It covers a wide range of topics in computer science and information technology, from image processing, database applications and data mining, to grid and cloud computing, bioinformatics and many more. The intelligent tools discussed, e.g. swarm intelligence, artificial intelligence, evolutionary algorithms, and bio-inspired algorithms, are currently being applied to solve challenging problems in various domains.

This book focuses on metaheuristic methods and its applications to real-world problems in Engineering. The first part describes some key metaheuristic methods, such as Bat Algorithms, Particle Swarm Optimization, Differential Evolution, and Particle Collision Algorithms. Improved versions of these methods and strategies for parameter tuning are also presented, both of which are essential for the practical use of these important computational tools. The second part then applies metaheuristics to problems, mainly in Civil, Mechanical, Chemical, Electrical, and Nuclear Engineering. Other methods, such as the Flower Pollination Algorithm, Symbiotic Organisms Search, Cross-Entropy Algorithm, Artificial Bee Colonies, Population-Based Incremental Learning, Cuckoo Search, and Genetic Algorithms, are also presented. The book is rounded out by recently developed strategies, or hybrid improved versions of existing methods, such as the Lightning Optimization Algorithm, Differential Evolution with Particle Collisions, and Ant Colony Optimization with Dispersion - state-of-the-art approaches for the application of computational intelligence to engineering problems. The wide variety of methods and applications, as well as the original results to problems of practical engineering interest, represent the primary differentiation and distinctive quality of this book. Furthermore, it gathers contributions by authors from four countries - some of which are the original proponents of the methods presented - and 18 research centers around the globe.

The book includes selected high-quality research papers presented at the Third International Congress on Information and Communication Technology held at Brunel University, London on February 27-28, 2018. It discusses emerging topics pertaining to information and communication technology (ICT) for managerial applications, e-governance, e-agriculture, e-education and computing technologies, the Internet of Things (IOT), and e-mining. Written by experts and researchers working on ICT, the book is suitable for new researchers involved in advanced studies.

This book gathers a wealth of research contributions on recent advances in intelligent and distributed computing, and which present both architectural and algorithmic findings in these fields. A major focus is placed on new techniques and applications for evolutionary computation, swarm intelligence, multi-agent systems, multi-criteria optimization and Deep/Shallow machine learning models, all of which are approached as technological drivers to enable autonomous reasoning and decision-making in complex distributed environments. Part of the book is also devoted to new scheduling and resource allocation methods for distributed computing systems. The book represents the peer-reviewed proceedings of the 12th International Symposium on Intelligent Distributed Computing (IDC 2018), which was held in Bilbao, Spain, from October 15 to 17, 2018.

This book presents conjectural advances in big data analysis, machine learning and computational intelligence, as well as their potential applications in scientific computing. It discusses major issues pertaining to big data analysis using computational intelligence techniques, and the conjectural elements are supported by simulation and modelling applications to help address real-world problems. An extensive bibliography is provided at the end of each chapter. Further, the main content is supplemented by a wealth of figures, graphs, and tables, offering a valuable guide for researchers in the field of big data analytics and computational intelligence.

The book provides readers with a snapshot of the state of the art in the field of nature-inspired computing and its application in optimization. The approach is mainly practice-oriented: each bio-inspired technique or algorithm is introduced together with one of its possible applications. Applications cover a wide range of real-world optimization problems: from feature selection and image enhancement to scheduling and dynamic resource management, from wireless sensor networks and wiring network diagnosis to sports training planning and gene expression, from topology control and morphological filters to nutritional meal design and antenna array design. There are a few theoretical chapters comparing different existing techniques, exploring the advantages of nature-inspired computing over other methods, and investigating the mixing time of genetic algorithms. The book also introduces a wide range of algorithms, including the ant colony optimization, the bat algorithm, genetic algorithms, the collision-based optimization algorithm, the flower pollination algorithm, multi-agent systems and particle swarm optimization. This timely book is intended as a practice-oriented reference guide for students, researchers and professionals.

This edited volume is devoted to the now-ubiquitous use of computational models across most disciplines of engineering and science, led by a trio of world-renowned researchers in the field. Focused on recent advances of modeling and optimization techniques aimed at handling computationally-expensive engineering problems involving simulation models, this book will be an invaluable resource for specialists (engineers, researchers, graduate students) working in areas as diverse as electrical engineering, mechanical and structural engineering, civil engineering, industrial engineering, hydrodynamics, aerospace engineering, microwave and antenna engineering, ocean science and climate modeling, and the automotive industry, where design processes are heavily based on CPU-heavy computer simulations. Various techniques, such as knowledge-based optimization, adjoint sensitivity techniques, and fast replacement models (to name just a few) are explored in-depth along with an array of the latest techniques to optimize the efficiency of the simulation-driven design process. High-fidelity simulation models allow for accurate evaluations of the devices and systems, which is critical in the design process, especially to avoid costly prototyping stages. Despite this and other advantages, the use of simulation tools in the design process is quite challenging due to associated high computational cost. The steady increase of available computational resources does not always translate into the shortening of the design cycle because of the growing demand for higher accuracy and necessity to simulate larger and more complex systems. For this reason, automated simulation-driven design-while highly desirable-is difficult when using conventional numerical optimization routines which normally require a large number of system simulations, each one already expensive.