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Computational Intelligence Applied to Inverse Problems in Radiative Transfer

This book offers a careful selection of studies in optimization techniques based on artificial intelligence, applied to inverse problems in radiative transfer. In this book, the reader will find an in-depth exploration of heuristic optimization methods, each meticulously described and accompanied by historical context and natural process analogies.From simulated annealing and genetic algorithms to artificial neural networks, ant colony optimization, and particle swarms, this volume presents a wide range of heuristic methods. Additional approaches such as generalized extreme optimization, particle collision, differential evolution, Luus-Jaakola, and firefly algorithms are also discussed, providing a rich repertoire of tools for tackling challenging problems.While the applications showcased primarily focus on radiative transfer, their potential extends to various domains, particularly nonlinear and large-scale problems where traditional deterministic methods fall short. With clear and comprehensive presentations, this book empowers readers to adapt each method to their specific needs. Furthermore, practical examples of classical optimization problems and application suggestions are included to enhance your understanding.This book is suitable to any researcher or practitioner whose interests lie on optimization techniques based in artificial intelligence and bio-inspired algorithms, in fields like Applied Mathematics, Engineering, Computing, and cross-disciplinary areas.

Computational Intelligence Assisted Design: In Industrial Revolution 4.0

Computational Intelligence Assisted Design framework mobilises computational resources, makes use of multiple Computational Intelligence (CI) algorithms and reduces computational costs. This book provides examples of real-world applications of technology. Case studies have been used to show the integration of services, cloud, big data technology and space missions. It focuses on computational modelling of biological and natural intelligent systems, encompassing swarm intelligence, fuzzy systems, artificial neutral networks, artificial immune systems and evolutionary computation. This book provides readers with wide-scale information on CI paradigms and algorithms, inviting readers to implement and problem solve real-world, complex problems within the CI development framework. This implementation framework will enable readers to tackle new problems without difficulty through a few tested MATLAB source codes

Computational Intelligence Assisted Design: In Industrial Revolution 4.0

Computational Intelligence Assisted Design framework mobilises computational resources, makes use of multiple Computational Intelligence (CI) algorithms and reduces computational costs. This book provides examples of real-world applications of technology. Case studies have been used to show the integration of services, cloud, big data technology and space missions. It focuses on computational modelling of biological and natural intelligent systems, encompassing swarm intelligence, fuzzy systems, artificial neutral networks, artificial immune systems and evolutionary computation. This book provides readers with wide-scale information on CI paradigms and algorithms, inviting readers to implement and problem solve real-world, complex problems within the CI development framework. This implementation framework will enable readers to tackle new problems without difficulty through a few tested MATLAB source codes

Computational Intelligence-based Optimization Algorithms: From Theory to Practice

Computational intelligence-based optimization methods, also known as metaheuristic optimization algorithms, are a popular topic in mathematical programming. These methods have bridged the gap between various approaches and created a new school of thought to solve real-world optimization problems. In this book, we have selected some of the most effective and renowned algorithms in the literature. These algorithms are not only practical but also provide thought-provoking theoretical ideas to help readers understand how they solve optimization problems. Each chapter includes a brief review of the algorithm’s background and the fields it has been used in. Additionally, Python code is provided for all algorithms at the end of each chapter, making this book a valuable resource for beginner and intermediate programmers looking to understand these algorithms.

Computational Intelligence-based Optimization Algorithms: From Theory to Practice

Computational intelligence-based optimization methods, also known as metaheuristic optimization algorithms, are a popular topic in mathematical programming. These methods have bridged the gap between various approaches and created a new school of thought to solve real-world optimization problems. In this book, we have selected some of the most effective and renowned algorithms in the literature. These algorithms are not only practical but also provide thought-provoking theoretical ideas to help readers understand how they solve optimization problems. Each chapter includes a brief review of the algorithm’s background and the fields it has been used in. Additionally, Python code is provided for all algorithms at the end of each chapter, making this book a valuable resource for beginner and intermediate programmers looking to understand these algorithms.

Computational Intelligence, Cyber Security and Computational Models: Proceedings of ICC3, 2013 (Advances in Intelligent Systems and Computing #246)

This book contains cutting-edge research material presented by researchers, engineers, developers, and practitioners from academia and industry at the International Conference on Computational Intelligence, Cyber Security and Computational Models (ICC3) organized by PSG College of Technology, Coimbatore, India during December 19–21, 2013. The materials in the book include theory and applications to provide design, analysis, and modeling of the key areas. The book will be useful material for students, researchers, professionals, as well academicians in understanding current research trends and findings and future scope of research in computational intelligence, cyber security, and computational models.

Computational Intelligence, Cyber Security and Computational Models: Proceedings of ICC3 2015 (Advances in Intelligent Systems and Computing #412)

This book aims at promoting high-quality research by researchers and practitioners from academia and industry at the International Conference on Computational Intelligence, Cyber Security, and Computational Models ICC3 2015 organized by PSG College of Technology, Coimbatore, India during December 17 – 19, 2015. This book enriches with innovations in broad areas of research like computational modeling, computational intelligence and cyber security. These emerging inter disciplinary research areas have helped to solve multifaceted problems and gained lot of attention in recent years. This encompasses theory and applications, to provide design, analysis and modeling of the aforementioned key areas.

Computational Intelligence for Business Analytics (Studies in Computational Intelligence #953)

Corporate success has been changed by the importance of new developments in Business Analytics (BA) and furthermore by the support of computational intelligence- based techniques. This book opens a new avenues in these subjects, identifies key developments and opportunities. The book will be of interest for students, researchers and professionals to identify innovative ways delivered by Business Analytics based on computational intelligence solutions. They help elicit information, handle knowledge and support decision-making for more informed and reliable decisions even under high uncertainty environments.Computational Intelligence for Business Analytics has collected the latest technological innovations in the field of BA to improve business models related to Group Decision-Making, Forecasting, Risk Management, Knowledge Discovery, Data Breach Detection, Social Well-Being, among other key topics related to this field.

Computational Intelligence for Human Action Recognition (Chapman & Hall/CRC Computational Intelligence and Its Applications)

Human Action Recognition is a challenging area presently. The vigor of research effort directed towards this domain is self indicative of this. With the ever-increasing involvement of Computational Intelligence in our day to day applications, the necessity of human activity recognition has been able to make its presence felt to the concerned research community. The primary drive of such an effort is to equip the computing system capable of recognizing and interpreting human activities from posture, pose, gesture, facial expression etc. The intent of human activity recognition is a formidable component of cognitive science in which researchers are actively engaged of late. Features: A systematic overview of the state-of-the-art in computational intelligence techniques for human action recognition. Emphasized on different intelligent techniques to recognize different human actions. Discussed about the automation techniques to handle human action recognition. Recent research results and some pointers to future advancements in this arena. In the present endeavour the editors intend to come out with a compilation that reflects the concerns of relevant research community. The readers would be able to come across some of the latest findings of active researchers of the concerned field. It is anticipated that this treatise shall be useful to the readership encompassing students at undergraduate and postgraduate level, researchers active as well as aspiring, not to speak of the senior researchers.

Computational Intelligence for Human Action Recognition (Chapman & Hall/CRC Computational Intelligence and Its Applications)

Human Action Recognition is a challenging area presently. The vigor of research effort directed towards this domain is self indicative of this. With the ever-increasing involvement of Computational Intelligence in our day to day applications, the necessity of human activity recognition has been able to make its presence felt to the concerned research community. The primary drive of such an effort is to equip the computing system capable of recognizing and interpreting human activities from posture, pose, gesture, facial expression etc. The intent of human activity recognition is a formidable component of cognitive science in which researchers are actively engaged of late. Features: A systematic overview of the state-of-the-art in computational intelligence techniques for human action recognition. Emphasized on different intelligent techniques to recognize different human actions. Discussed about the automation techniques to handle human action recognition. Recent research results and some pointers to future advancements in this arena. In the present endeavour the editors intend to come out with a compilation that reflects the concerns of relevant research community. The readers would be able to come across some of the latest findings of active researchers of the concerned field. It is anticipated that this treatise shall be useful to the readership encompassing students at undergraduate and postgraduate level, researchers active as well as aspiring, not to speak of the senior researchers.

Computational Intelligence for Network Structure Analytics

This book presents the latest research advances in complex network structure analytics based on computational intelligence (CI) approaches, particularly evolutionary optimization. Most if not all network issues are actually optimization problems, which are mostly NP-hard and challenge conventional optimization techniques. To effectively and efficiently solve these hard optimization problems, CI based network structure analytics offer significant advantages over conventional network analytics techniques. Meanwhile, using CI techniques may facilitate smart decision making by providing multiple options to choose from, while conventional methods can only offer a decision maker a single suggestion. In addition, CI based network structure analytics can greatly facilitate network modeling and analysis. And employing CI techniques to resolve network issues is likely to inspire other fields of study such as recommender systems, system biology, etc., which will in turn expand CI’s scope and applications.As a comprehensive text, the book covers a range of key topics, including network community discovery, evolutionary optimization, network structure balance analytics, network robustness analytics, community-based personalized recommendation, influence maximization, and biological network alignment.Offering a rich blend of theory and practice, the book is suitable for students, researchers and practitioners interested in network analytics and computational intelligence, both as a textbook and as a reference work.

Computational Intelligence for Wireless Sensor Networks: Principles and Applications

Computational Intelligence for Wireless Sensor Networks: Principles and Applications provides an integrative overview of the computational intelligence (CI) in wireless sensor networks and enabled technologies. It aims to demonstrate how the paradigm of computational intelligence can benefit Wireless Sensor Networks (WSNs) and sensor-enabled technologies to overcome their existing issues. This book provides extensive coverage of the multiple design challenges of WSNs and associated technologies such as clustering, routing, media access, security, mobility, and design of energy-efficient network operations. It also describes various CI strategies such as fuzzy computing, evolutionary computing, reinforcement learning, artificial intelligence, swarm intelligence, teaching learning-based optimization, etc. It also discusses applying the techniques mentioned above in wireless sensor networks and sensor-enabled technologies to improve their design. The book offers comprehensive coverage of related topics, including: Emergence of intelligence in wireless sensor networks Taxonomy of computational intelligence Detailed discussion of various metaheuristic techniques Development of intelligent MAC protocols Development of intelligent routing protocols Security management in WSNs This book mainly addresses the challenges pertaining to the development of intelligent network systems via computational intelligence. It provides insights into how intelligence has been pursued and can be further integrated in the development of sensor-enabled applications.

Computational Intelligence for Wireless Sensor Networks: Principles and Applications

Computational Intelligence for Wireless Sensor Networks: Principles and Applications provides an integrative overview of the computational intelligence (CI) in wireless sensor networks and enabled technologies. It aims to demonstrate how the paradigm of computational intelligence can benefit Wireless Sensor Networks (WSNs) and sensor-enabled technologies to overcome their existing issues. This book provides extensive coverage of the multiple design challenges of WSNs and associated technologies such as clustering, routing, media access, security, mobility, and design of energy-efficient network operations. It also describes various CI strategies such as fuzzy computing, evolutionary computing, reinforcement learning, artificial intelligence, swarm intelligence, teaching learning-based optimization, etc. It also discusses applying the techniques mentioned above in wireless sensor networks and sensor-enabled technologies to improve their design. The book offers comprehensive coverage of related topics, including: Emergence of intelligence in wireless sensor networks Taxonomy of computational intelligence Detailed discussion of various metaheuristic techniques Development of intelligent MAC protocols Development of intelligent routing protocols Security management in WSNs This book mainly addresses the challenges pertaining to the development of intelligent network systems via computational intelligence. It provides insights into how intelligence has been pursued and can be further integrated in the development of sensor-enabled applications.

Computational Intelligence in Biomedical Engineering

As in many other fields, biomedical engineers benefit from the use of computational intelligence (CI) tools to solve complex and non-linear problems. The benefits could be even greater if there were scientific literature that specifically focused on the biomedical applications of computational intelligence techniques. The first comprehensive field-

Computational Intelligence in Data Science: Third IFIP TC 12 International Conference, ICCIDS 2020, Chennai, India, February 20–22, 2020, Revised Selected Papers (IFIP Advances in Information and Communication Technology #578)

This book constitutes the refereed post-conference proceedings of the Third IFIP TC 12 International Conference on Computational Intelligence in Data Science, ICCIDS 2020, held in Chennai, India, in February 2020.The 19 revised full papers and 8 revised short papers presented were carefully reviewed and selected from 94 submissions. The papers are organized in the following topical sections: computational intelligence for text analysis; computational intelligence for image and video analysis; and data science.

Computational Intelligence in Economics and Finance (Advanced Information Processing)

Due to the ability to handle specific characteristics of economics and finance forecasting problems like e.g. non-linear relationships, behavioral changes, or knowledge-based domain segmentation, we have recently witnessed a phenomenal growth of the application of computational intelligence methodologies in this field. In this volume, Chen and Wang collected not just works on traditional computational intelligence approaches like fuzzy logic, neural networks, and genetic algorithms, but also examples for more recent technologies like e.g. rough sets, support vector machines, wavelets, or ant algorithms. After an introductory chapter with a structural description of all the methodologies, the subsequent parts describe novel applications of these to typical economics and finance problems like business forecasting, currency crisis discrimination, foreign exchange markets, or stock markets behavior.

Computational Intelligence in Emerging Technologies for Engineering Applications (Studies in Computational Intelligence #872)

This book explores applications of computational intelligence in key and emerging fields of engineering, especially with regard to condition monitoring and fault diagnosis, inverse problems, decision support systems and optimization. These applications can be beneficial in a broad range of contexts, including: water distribution networks, manufacturing systems, production and storage of electrical energy, heat transfer, acoustic levitation, uncertainty and robustness of infinite-dimensional objects, fatigue failure prediction, autonomous navigation, nanotechnology, and the analysis of technological development indexes. All applications, mathematical and computational tools, and original results are presented using rigorous mathematical procedures. Further, the book gathers contributions by respected experts from 22 different research centers and eight countries: Brazil, Cuba, France, Hungary, India, Japan, Romania and Spain. The book is intended for use in graduate courses on applied computation, applied mathematics, and engineering, where tools like computational intelligence and numerical methods are applied to the solution of real-world problems in emerging areas of engineering.

Computational Intelligence in Expensive Optimization Problems (Adaptation, Learning, and Optimization #2)

In modern science and engineering, laboratory experiments are replaced by high fidelity and computationally expensive simulations. Using such simulations reduces costs and shortens development times but introduces new challenges to design optimization process. Examples of such challenges include limited computational resource for simulation runs, complicated response surface of the simulation inputs-outputs, and etc. Under such difficulties, classical optimization and analysis methods may perform poorly. This motivates the application of computational intelligence methods such as evolutionary algorithms, neural networks and fuzzy logic, which often perform well in such settings. This is the first book to introduce the emerging field of computational intelligence in expensive optimization problems. Topics covered include: dedicated implementations of evolutionary algorithms, neural networks and fuzzy logic. reduction of expensive evaluations (modelling, variable-fidelity, fitness inheritance), frameworks for optimization (model management, complexity control, model selection), parallelization of algorithms (implementation issues on clusters, grids, parallel machines), incorporation of expert systems and human-system interface, single and multiobjective algorithms, data mining and statistical analysis, analysis of real-world cases (such as multidisciplinary design optimization). The edited book provides both theoretical treatments and real-world insights gained by experience, all contributed by leading researchers in the respective fields. As such, it is a comprehensive reference for researchers, practitioners, and advanced-level students interested in both the theory and practice of using computational intelligence for expensive optimization problems.

Computational Intelligence in Industrial Application: Proceedings of the 2014 Pacific-Asia Workshop on Computer Science in Industrial Application (CIIA 2014), Singapore, December 8-9, 2014

These proceedings of the 2014 Pacific-Asia Workshop on Computational Intelligence in Industrial Application (CIIA 2014) include 81 peer-reviewed papers. The topics covered in the book include: (1) Computer Intelligence, (2) Application of Computer Science and Communication, (3) Industrial Engineering, Product Design and Manufacturing, (4) Automatio

Computational Intelligence in Machine Learning: Proceedings of the 2nd International Conference ICCIML 2022 (Lecture Notes in Electrical Engineering #1106)

This volumes comprises select proceedings of the International Conference on Computational Intelligence in Machine Learning (ICCIML 2022). The contents cover latest research trends and developments in the areas of machine learning, smart cities, IoT, Artificial Intelligence, cyber physical systems, cybernetics, data science, neural network, cognition, among others. It also addresses the comprehensive nature of computational intelligence, AI, ML and DL to emphasize its character in modelling, identification, optimization, prediction, forecasting, and control of future intelligent systems. This volume will be a useful guide to those working as researchers in academia and industry by presenting in-depth fundamental research contributions from a methodological/application perspective in understanding Artificial intelligence and machine learning approaches and their capabilities in solving diverse range of problems in industries and its real-world applications.

Computational Intelligence in Music, Sound, Art and Design: 8th International Conference, EvoMUSART 2019, Held as Part of EvoStar 2019, Leipzig, Germany, April 24–26, 2019, Proceedings (Lecture Notes in Computer Science #11453)

This book constitutes the refereed proceedings of the 8th International Conference on Evolutionary Computation in Combinatorial Optimization, EvoMUSART 2019, held in Leipzig, Germany, in April 2019, co-located with the Evo*2019 events EuroGP, EvoCOP and EvoApplications. The 16 revised full papers presented were carefully reviewed and selected from 24 submissions. The papers cover a wide range of topics and application areas, including: visual art and music generation, analysis, and interpretation; sound synthesis; architecture; video; poetry; design; and other creative tasks.

Computational Intelligence in Music, Sound, Art and Design: 6th International Conference, EvoMUSART 2017, Amsterdam, The Netherlands, April 19–21, 2017, Proceedings (Lecture Notes in Computer Science #10198)

This book constitutes the refereed proceedings of the 6th International Conference on Evolutionary Computation in Combinatorial Optimization, EvoMUSART 2017, held in Amsterdam, The Netherlands, in April 2017, co-located with the Evo*2017 events EuroGP, EvoCOP and EvoApplications. The 24 revised full papers presented were carefully reviewed and selected from 29 submissions. The papers cover a wide range of topics and application areas, including: generative approaches to music, graphics, game content, and narrative; music information retrieval; computational aesthetics; the mechanics of interactive evolutionary computation; computer-aided design; and the art theory of evolutionary computation.

Computational Intelligence in Optimization: Applications and Implementations (Adaptation, Learning, and Optimization #7)

Computational Intelligence in Reliability Engineering: New Metaheuristics, Neural and Fuzzy Techniques in Reliability (Studies in Computational Intelligence #40)

This volume includes chapters presenting applications of different metaheuristics in reliability engineering, including ant colony optimization, great deluge algorithm, cross-entropy method and particle swarm optimization. It also presents chapters devoted to cellular automata and support vector machines, and applications of artificial neural networks, a powerful adaptive technique that can be used for learning, prediction and optimization. Several chapters describe aspects of imprecise reliability and applications of fuzzy and vague set theory.

Computational Intelligence in Reliability Engineering: Evolutionary Techniques in Reliability Analysis and Optimization (Studies in Computational Intelligence #39)

This book covers the recent applications of computational intelligence techniques in reliability engineering. This volume contains a survey of the contributions made to the optimal reliability design literature in recent years. It also contains chapters devoted to different applications of a genetic algorithm in reliability engineering and to combinations of this algorithm with other computational intelligence techniques.