This book brings together a rich selection of studies in mathematical modeling and computational intelligence, with application in several fields of engineering, like automation, biomedical, chemical, civil, electrical, electronic, geophysical and mechanical engineering, on a multidisciplinary approach. Authors from five countries and 16 different research centers contribute with their expertise in both the fundamentals and real problems applications based upon their strong background on modeling and computational intelligence. The reader will find a wide variety of applications, mathematical and computational tools and original results, all presented with rigorous mathematical procedures. This work is intended for use in graduate courses of engineering, applied mathematics and applied computation where tools as mathematical and computational modeling, numerical methods and computational intelligence are applied to the solution of real problems.

This book collects papers presented at the International Conference on Mathematical Modelling and Computational Intelligence Techniques (ICMMCIT) 2021, held at the Department of Mathematics, The Gandhigram Rural Institute (Deemed to be University), Gandhigram, Tamil Nadu, India, from 10–12 February 2021. Significant contributions from renowned researchers from fields of applied analysis, mathematical modelling and computing techniques have been received for this conference. Chapters emphasize on the research of computational nature focusing on new algorithms, their analysis and numerical results, as well as applications in physical, biological, social, and behavioural sciences. The accepted papers are organized in topical sections as mathematical modelling, image processing, control theory, graphs and networks, and inventory control.

This book presents new knowledge and recent developments in all aspects of computational techniques, mathematical modeling, energy systems, applications of fuzzy sets and intelligent computing. The book is a collection of best selected research papers presented at the International Conference on “Mathematical Modeling, Computational Intelligence Techniques and Renewable Energy,” organized by the Department of Mathematics, Pandit Deendayal Petroleum University, in association with Forum for Interdisciplinary Mathematics, Institution of Engineers (IEI) – Gujarat and Computer Society of India (CSI) – Ahmedabad. The book provides innovative works of researchers, academicians and students in the area of interdisciplinary mathematics, statistics, computational intelligence and renewable energy.

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.

Technological tools and computational techniques have enhanced the healthcare industry. These advancements have led to significant progress and novel opportunities for biomedical engineering. Nature-Inspired Intelligent Techniques for Solving Biomedical Engineering Problems is a pivotal reference source for emerging scholarly research on trends and techniques in the utilization of nature-inspired approaches in biomedical engineering. Featuring extensive coverage on relevant areas such as artificial intelligence, clinical decision support systems, and swarm intelligence, this publication is an ideal resource for medical practitioners, professionals, students, engineers, and researchers interested in the latest developments in biomedical technologies.

Artificial Intelligence (AI) is defined as the simulation of human intelligence through the mimicking of the human brain for analysis, modeling, and decision‐making. Science and engineering problem solving requires modeling of physical phenomena, and humans approach the solution of scientific and engineering problems differently from other problems. Artificial Intelligence for Science and Engineering Applications addresses the unique differences in how AI should be developed and used in science and engineering. Through the inclusion of definitions and detailed examples, this book describes the actual and realistic requirements as well as what characteristics must be avoided for correct and successful science and engineering applications of AI. This book: Offers a brief history of AI and covers science and engineering applications Explores the modeling of physical phenomena using AI Discusses explainable AI (XAI) applications Covers the ethics of AI in science and engineering Features real‐world case studies Offering a probing view into the unique nature of scientific and engineering exploration, this book will be of interest to generalists and experts looking to expand their understanding of how AI can better tackle and advance technology and developments in scientific and engineering disciplines.

Due to the growing use of web applications and communication devices, the use of data has increased throughout various industries, including business and healthcare. It is necessary to develop specific software programs that can analyze and interpret large amounts of data quickly in order to ensure adequate usage and predictive results. Cognitive Analytics: Concepts, Methodologies, Tools, and Applications provides emerging perspectives on the theoretical and practical aspects of data analysis tools and techniques. It also examines the incorporation of pattern management as well as decision-making and prediction processes through the use of data management and analysis. Highlighting a range of topics such as natural language processing, big data, and pattern recognition, this multi-volume book is ideally designed for information technology professionals, software developers, data analysts, graduate-level students, researchers, computer engineers, software engineers, IT specialists, and academicians.

This book presents recent research into developing and applying computational tools to estimate the performance and safety of hydraulic structures from the planning and construction stage to the service period. Based on the results of a close collaboration between the author and his colleagues, friends, students and field engineers, it shows how to achieve a good correlation between numerical computation and the actual in situ behavior of hydraulic structures. The book’s heuristic and visualized style disseminates the philosophy and road map as well as the findings of the research. The chapters reflect the various aspects of the three typical and practical methods (the finite element method, the block element method, the composite element method) that the author has been working on and made essential contributions to since the 1980s. This book is an advanced continuation of Hydraulic Structures by the same author, published by Springer in 2015.

This book gives comprehensive insights into the application of AI, machine learning, and deep learning in developing efficient and optimal surveillance systems for both indoor and outdoor environments, addressing the evolving security challenges in public and private spaces. Mathematical Models Using Artificial Intelligence for Surveillance Systems aims to collect and publish basic principles, algorithms, protocols, developing trends, and security challenges and their solutions for various indoor and outdoor surveillance applications using artificial intelligence (AI). The book addresses how AI technologies such as machine learning (ML), deep learning (DL), sensors, and other wireless devices could play a vital role in assisting various security agencies. Security and safety are the major concerns for public and private places in every country. Some places need indoor surveillance, some need outdoor surveillance, and, in some places, both are needed. The goal of this book is to provide an efficient and optimal surveillance system using AI, ML, and DL-based image processing. The blend of machine vision technology and AI provides a more efficient surveillance system compared to traditional systems. Leading scholars and industry practitioners are expected to make significant contributions to the chapters. Their deep conversations and knowledge, which are based on references and research, will result in a wonderful book and a valuable source of information.

The subject “Systems sciences and cybernetics” is the outcome of the convergence of a number of trends in a larger current of thought devoted to the growing complexity of (primarily social) objects and arising in response to the need for globalized treatment of such objects. This has been magnified by the proliferation and publication of all manner of quantitative scientific data on such objects, advances in the theories on their inter-relations, the enormous computational capacity provided by IT hardware and software and the critical revisiting of subject-object interaction, not to mention the urgent need to control the efficiency of complex systems, where “efficiency” is understood to mean the ability to find a solution to many social problems, including those posed on a planetary scale. The result has been the forging of a new, academically consolidated scientific trend going by the name of Systems Theory and Cybernetics, with a comprehensive, multi-disciplinary focus and therefore apt for understanding realities still regarded to be inescapably chaotic. This subject entry is subdivided into four sections. The first, an introduction to systemic theories, addresses the historic development of the most commonly used systemic approaches, from new concepts such as the so-called “geometry of thinking” or the systemic treatment of “non-systemic identities” to the taxonomic, entropic, axiological and ethical problems deriving from a general “systemic-cybernetic” conceit. Hence, the focus in this section is on the historic and philosophical aspects of the subject. Moreover, it may be asserted today that, beyond a shadow of a doubt, problems, in particular problems deriving from human interaction but in general any problem regardless of its nature, must be posed from a systemic perspective, for otherwise the obstacles to their solution are insurmountable. Reaching such a perspective requires taking at least the following well-known steps: a) statement of the problem from the determinant variables or phenomena; b) adoption of theoretical models showing the interrelationships among such variables; c) use of the maximum amount of – wherever possible quantitative – information available on each; d) placement of the set of variables in an environment that inevitably pre-determines the problem. That epistemology would explain the substantial development of the systemic-cybernetic approach in recent decades. The articles in the second section deal in particular with the different methodological approaches developed when confronting real problems, from issues that affect humanity as a whole to minor but specific questions arising in human organizations. Certain sub-themes are discussed by the various authors – always from a didactic vantage –, including: problem discovery and diagnosis and development of the respective critical theory; the design of ad hoc strategies and methodologies; the implementation of both qualitative (soft system methodologies) and formal and quantitative (such as the “General System Problem Solver” or the “axiological-operational” perspective) approaches; cross-disciplinary integration; and suitable methods for broaching psychological, cultural and socio-political dynamisms. The third section is devoted to cybernetics in the present dual meaning of the term: on the one hand, control of the effectiveness of communication and actions, and on the other, the processes of self-production of knowledge through reflection and the relationship between the observing subject and the observed object when the latter is also observer and the former observed. Known as “second order cybernetics”, this provides an avenue for rethinking the validity of knowledge, such as for instance when viewed through what is known as “bipolar feedback”: processes through which interactions create novelty, complexity and diversity. Finally, the fourth section centres around artificial and computational intelligence, addressing sub-themes such as “neural networks”, the “simulated annealing” that ranges from statistical thermodynamics to combinatory problem-solving, such as in the explanation of the role of adaptive systems, or when discussing the relationship between biological and computational intelligence.