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Computational Intelligence Applications in Modeling and Control (Studies in Computational Intelligence #575)
by Ahmad Taher Azar Sundarapandian VaidyanathanThe development of computational intelligence (CI) systems was inspired by observable and imitable aspects of intelligent activity of human being and nature. The essence of the systems based on computational intelligence is to process and interpret data of various nature so that that CI is strictly connected with the increase of available data as well as capabilities of their processing, mutually supportive factors. Developed theories of computational intelligence were quickly applied in many fields of engineering, data analysis, forecasting, biomedicine and others. They are used in images and sounds processing and identifying, signals processing, multidimensional data visualization, steering of objects, analysis of lexicographic data, requesting systems in banking, diagnostic systems, expert systems and many other practical implementations. This book consists of 16 contributed chapters by subject experts who are specialized in the various topics addressed in this book. The special chapters have been brought out in the broad areas of Control Systems, Power Electronics, Computer Science, Information Technology, modeling and engineering applications. Special importance was given to chapters offering practical solutions and novel methods for the recent research problems in the main areas of this book, viz. Control Systems, Modeling, Computer Science, IT and engineering applications. This book will serve as a reference book for graduate students and researchers with a basic knowledge of control theory, computer science and soft-computing techniques. The resulting design procedures are emphasized using Matlab/Simulink software.
Computational Intelligence Applications to Option Pricing, Volatility Forecasting and Value at Risk (Studies in Computational Intelligence #697)
by Tharam Dillon Fahed Mostafa Elizabeth ChangThis book demonstrates the power of neural networks in learning complex behavior from the underlying financial time series data. The results presented also show how neural networks can successfully be applied to volatility modeling, option pricing, and value-at-risk modeling. These features mean that they can be applied to market-risk problems to overcome classic problems associated with statistical models.
Computational Intelligence Applied to Decision-Making in Uncertain Environments (Studies in Computational Intelligence #1195)
by Janusz Kacprzyk Pedro Yobanis Piñero Pérez Iliana Pérez Pupo Rafael Esteban Bello PérezThis book is dedicated to all those interested in the application of computational intelligence techniques for decision-making in uncertain environments. The book is organized into four parts. The first part groups together four works related to conversational systems and decision-making using generative artificial intelligence. The second part includes four articles associated with decision-making in project-oriented environments. The third part includes three works related to decision-making in human health environments and decision-making in sports training. The fourth part of the book contains three articles associated with business decision-making. This book combines different artificial intelligence techniques for solving decision-making problems, among which the following stand out: generative artificial intelligence, linguistic data summarization techniques, neutrosophic theory, computing with words, among other techniques. The techniques proposed in the book aim to simulate human tolerance in decision-making processes in environments with uncertainty and imprecision. The authors of the book stand out for their extensive experience in the development of basic and applied applications of computational intelligence. The authors Pedro Y. Piñero Pérez, Iliana Pérez Pupo, Janusz Kacprzyk, and Rafael E. Bello Pérez have published several books associated with artificial intelligence and applied computational intelligence. They continue to work on fundamental and applied research on different artificial intelligence techniques to assist decision-making in different areas of knowledge. The authors thank all the engineers, professors, and researchers without whose efforts this book could not have been written.
Computational Intelligence Applied to Inverse Problems in Radiative Transfer
by Antônio José da Silva Neto Haroldo Fraga de Campos Velho José Carlos BecceneriThis 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
by Yun Li Yi ChenComputational 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 Methods for Bioinformatics and Biostatistics: 10th International Meeting, CIBB 2013, Nice, France, June 20-22, 2013, Revised Selected Papers (Lecture Notes in Computer Science #8452)
by Enrico Formenti Roberto Tagliaferri Ernst WitThis book constitutes the thoroughly refereed post-conference proceedings of the 10th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2013, held in Nice, France in June 2013. The 19 revised full papers presented were carefully reviewed and selected from 35 submissions. The papers are organized in topical sections on bioinformatics, biostatistics, knowledge based medicine, and data integration and analysis in omic-science.
Computational Intelligence Methods for Bioinformatics and Biostatistics: 12th International Meeting, CIBB 2015, Naples, Italy, September 10-12, 2015, Revised Selected Papers (Lecture Notes in Computer Science #9874)
by Stefano Rovetta Claudia Angelini Paola M. V. RancoitaThis book constitutes the thoroughly refereed post-conference proceedings of the 12th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2015, held in Naples, Italy, in September, 2015. The 21 revised full papers presented were carefully reviewed and selected from 24 submissions. They present problems concerning computational techniques in bioinformatics, systems biology and medical informatics discussing cutting edge methodologies and accelerate life science discoveries, as well as novel challenges with an high impact on molecular biology and translational medicine.
Computational Intelligence Methods for Bioinformatics and Biostatistics: 13th International Meeting, CIBB 2016, Stirling, UK, September 1-3, 2016, Revised Selected Papers (Lecture Notes in Computer Science #10477)
by David Gilbert Roberto Tagliaferri Andrea Bracciali Giulio CaravagnaThis book constitutes the thoroughly refereed post-conference proceedings of the 10th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2013, held in Nice, France in June 2013. The 19 revised full papers presented were carefully reviewed and selected from 35 submissions. The papers are organized in topical sections on bioinformatics, biostatistics, knowledge based medicine, and data integration and analysis in omic-science.
Computational Intelligence Methods for Bioinformatics and Biostatistics: 14th International Meeting, CIBB 2017, Cagliari, Italy, September 7-9, 2017, Revised Selected Papers (Lecture Notes in Computer Science #10834)
by Leif Peterson Roberto Tagliaferri Alberto Policriti Andrea Bracciali Massimo Bartoletti Annalisa Barla Gunnar W. KlauThis book constitutes the thoroughly refereed post-conference proceedings of the 14th International Meeting on Computational. Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2017, held in Cagliari, Italy, in September 2017.The 19 revised full papers presented were carefully reviewed and selected from 44 submissions. The papers deal with the application of computational intelligence to open problems in bioinformatics, biostatistics, systems and synthetic biology, medical informatics, computational approaches to life sciences in general.
Computational Intelligence Methods for Bioinformatics and Biostatistics: 15th International Meeting, CIBB 2018, Caparica, Portugal, September 6–8, 2018, Revised Selected Papers (Lecture Notes in Computer Science #11925)
by Maria Raposo Paulo Ribeiro Angelo Ciaramella Susana Sério Antonino StaianoThis book constitutes the thoroughly refereed post-conference proceedings of the 15th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics., CIBB 2018, held in Caparica, Portugal, in September 2018. The 32 revised full papers were carefully reviewed and selected from 51 submissions. The papers present current trends at the edge of computer and life sciences, the application of computational intelligence to a system and synthetic biology and the consequent impact on innovative medicine were presented. Theoretical and experimental biologists also presented novel challenges and fostered multidisciplinary collaboration aiming to blend theory and practice, where the founding theories of the techniques used for modelling and analyzing biological systems are investigated and used for practical applications and the supporting technologies.
Computational Intelligence Methods for Bioinformatics and Biostatistics: 16th International Meeting, CIBB 2019, Bergamo, Italy, September 4–6, 2019, Revised Selected Papers (Lecture Notes in Computer Science #12313)
by Luca Manzoni Paolo Cazzaniga Daniela Besozzi Ivan MerelliThis book constitutes revised selected papers from the 16th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2019, which was held in Bergamo, Italy, during September 4-6, 2019. The 28 full papers presented in this volume were carefully reviewed and selected from 55 submissions. The papers are grouped in topical sections as follows: Computational Intelligence Methods for Bioinformatics and Biostatistics; Algebraic and Computational Methods for the Study of RNA Behaviour; Intelligence methods for molecular characterization medicine; Machine Learning in Healthcare Informatics and Medical Biology; Modeling and Simulation Methods for Computational Biology and Systems Medicine.
Computational Intelligence Methods for Bioinformatics and Biostatistics: 17th International Meeting, CIBB 2021, Virtual Event, November 15–17, 2021, Revised Selected Papers (Lecture Notes in Computer Science #13483)
by Paolo Cazzaniga Davide Chicco Angelo Facchiano Erica Tavazzi Enrico Longato Martina Vettoretti Anna Bernasconi Simone AvesaniThis book constitutes revised selected papers from the 17th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2021, which was held virtually during November 15–17, 2021. The 19 papers included in these proceedings were carefully reviewed and selected from 26 submissions, and they focus on bioinformatics, computational biology, health informatics, cheminformatics, biotechnology, biostatistics, and biomedical imaging.
Computational Intelligence Methods for Bioinformatics and Biostatistics: 18th International Meeting, CIBB 2023, Padova, Italy, September 6–8, 2023, Revised Selected Papers (Lecture Notes in Computer Science #14513)
by Erica Tavazzi Enrico Longato Martina Vettoretti Giacomo Baruzzo Massimo BellatoThe book constitutes the refereed post-conference proceedings of the 18th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2023, held in Padova, Italy, during September 6–8, 2023. The 23 full papers presented in these proceedings were carefully reviewed and selected from 24 submissions. They focuses on topics such as machine learning in healthcare informatics and medical biology; machine learning explainability in medical imaging; prediction uncertainty in machine learning; advanced statistical and computational methodologies for single-cell omics data; present and future research in bioinformatics; distributed computing in bioinformatics and computational biology; and modelling and simulation methods for computational biology and systems medicine.
Computational Intelligence Methods for Bioinformatics and Biostatistics: 19th International Meeting, CIBB 2024, Benevento, Italy, September 4–6, 2024, Revised Selected Papers (Lecture Notes in Computer Science #15276)
by Luigi Cerulo Francesco Napolitano Francesco Bardozzo Lu Cheng Annalisa Occhipinti Stefano M. PagnottaThis volume LNCS 15276 constitutes the revised selected papers of the 19th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2024, held in Benevento, Italy, during September 4–6, 2024. The 24 full papers and 3 short papers were carefully reviewed and selected from 28 submissions. They were organized in the following topical sections: Bioinformatics; Medical Informatics; Natural Language Processing (NLP) and Large Language Models (LLM) for Unstructured Data in Health Informatics; Modeling and Simulation Methods for Computational Biology and Systems Medicine; Machine Learning for Structured Data in Clinical Informatics and Medical Biology; Computational Intelligence in Personalized Medicine; and Computational Structural Bioinformatics.
Computational Intelligence Methods for Green Technology and Sustainable Development: Proceedings of the International Conference GTSD2022 (Lecture Notes in Networks and Systems #567)
by Yo-Ping Huang Wen-June Wang Hoang An Quoc Hieu-Giang Le Hoai-Nam QuachThis book provides readers with peer-reviewed research papers presented at the 6th International Conference on Green Technology and Sustainable Development (GTSD) held in Nha Trang City, Vietnam, from July 29 to 30, 2022. The book is original work of researchers from academia and industry focusing on the theme “Green technology and sustainable development in Industrial Revolution 4.0” not only to raise awareness of the vital importance of sustainability in education, technology, and economic development, but also to highlight the essential roles of technology innovation for the green future. The book presents a wide range of research aspects including energy engineering, electric power systems, renewable energy systems, automatic control engineering, robotics, vehicle engineering, material engineering, construction engineering, mechanical engineering, vibrations, computational analysis, numerical investigation, system failure, technological solutions in health care, and so on. Through thorough research basing on both experimental and numerical methods, the authors feature either solutions for existing problems or optimization and improvement for performance of existing methods. The collected research results could be useful alternatives and implications for industry experts, research institutions, universities, and all others who share a common interest in the future global sustainable development.
Computational Intelligence Methods for Green Technology and Sustainable Development: Proceedings of the International Conference GTSD2024, Volume 1 (Lecture Notes in Networks and Systems #1195)
by Yo-Ping Huang Wen-June Wang Hieu-Giang Le An-Quoc HoangThis book is presented in two volumes, featuring peer-reviewed research papers from the 7th International Conference on Green Technology and Sustainable Development (GTSD), held in Ho Chi Minh City, Vietnam, from July 25 to 26, 2024. It highlights original research by experts from both academia and industry, centered on the theme of "Green Technology and Sustainable Development in the Industrial Revolution 4.0." The book underscores the critical importance of sustainability in education, technology, and economic development, while also showcasing the vital role of technological innovation in creating a greener future. The papers documented in this book cover a broad range of topics, including renewable energy systems, smart grids, artificial intelligence, robotics and intelligent systems, and computational intelligence, all with a focus on sustainable development, climate change mitigation, and environmental policy. These studies showcase cutting-edge technologies and innovative ideas related to green technology, offering actionable insights for advancing sustainable development across various sectors. The authors present research based on both experimental and numerical methods, offering solutions to current problems and optimizing existing methods. The insights and findings provided are valuable for industry experts, research institutions, universities, and anyone interested in advancing global sustainable development.
Computational Intelligence Methods for Green Technology and Sustainable Development: Proceedings of the International Conference GTSD2024, Volume 2 (Lecture Notes in Networks and Systems #1199)
by Yo-Ping Huang Wen-June Wang Hieu-Giang Le An-Quoc HoangThis book is presented in two volumes, featuring peer-reviewed research papers from the 7th International Conference on Green Technology and Sustainable Development (GTSD), held in Ho Chi Minh City, Vietnam, from July 25 to 26, 2024. It highlights original research by experts from both academia and industry, centered on the theme of "Green Technology and Sustainable Development in the Industrial Revolution 4.0." The book underscores the critical importance of sustainability in education, technology, and economic development, while also showcasing the vital role of technological innovation in creating a greener future. The papers documented in this book cover a broad range of topics, including renewable energy systems, smart grids, artificial intelligence, robotics and intelligent systems, and computational intelligence, all with a focus on sustainable development, climate change mitigation, and environmental policy. These studies showcase cutting-edge technologies and innovative ideas related to green technology, offering actionable insights for advancing sustainable development across various sectors. The authors present research based on both experimental and numerical methods, offering solutions to current problems and optimizing existing methods. The insights and findings provided are valuable for industry experts, research institutions, universities, and anyone interested in advancing global sustainable development.
Computational Intelligence Methods for Super-Resolution in Image Processing Applications
by Anand Deshpande Navid Razmjooy Vania V. EstrelaThis book explores the application of deep learning techniques within a particularly difficult computational type of computer vision (CV) problem ─ super-resolution (SR). The authors present and discuss ways to apply computational intelligence (CI) methods to SR. The volume also explores the possibility of using different kinds of CV techniques to develop and enhance the tools/processes related to SR. The application areas covered include biomedical engineering, healthcare applications, medicine, histology, and material science. The book will be a valuable reference for anyone concerned with multiple multimodal images, especially professionals working in remote sensing, nanotechnology and immunology at research institutes, healthcare facilities, biotechnology institutions, agribusiness services, veterinary facilities, and universities.
Computational Intelligence Methods in COVID-19: Surveillance, Prevention, Prediction and Diagnosis (Studies in Computational Intelligence #923)
by Khalid RazaThe novel coronavirus disease 2019 (COVID-19) pandemic has posed a major threat to human life and health. This book is beneficial for interdisciplinary students, researchers, and professionals to understand COVID-19 and how computational intelligence can be used for the purpose of surveillance, control, prevention, prediction, diagnosis, and potential treatment of the disease. The book contains different aspects of COVID-19 that includes fundamental knowledge, epidemic forecast models, surveillance and tracking systems, IoT- and IoMT-based integrated systems for COVID-19, social network analysis systems for COVID-19, radiological images (CT, X-ray) based diagnosis system, and computational intelligence and in silico drug design and drug repurposing methods against COVID-19 patients. The contributing authors of this volume are experts in their fields and they are from various reputed universities and institutions across the world. This volume is a valuable and comprehensive resource for computer and data scientists, epidemiologists, radiologists, doctors, clinicians, pharmaceutical professionals, along with graduate and research students of interdisciplinary and multidisciplinary sciences.
Computational Intelligence Paradigms for Optimization Problems Using MATLAB®/SIMULINK®
by S. Sumathi L. Ashok Kumar Surekha. PConsidered one of the most innovative research directions, computational intelligence (CI) embraces techniques that use global search optimization, machine learning, approximate reasoning, and connectionist systems to develop efficient, robust, and easy-to-use solutions amidst multiple decision variables, complex constraints, and tumultuous environments. CI techniques involve a combination of learning, adaptation, and evolution used for intelligent applications. Computational Intelligence Paradigms for Optimization Problems Using MATLAB®/ Simulink® explores the performance of CI in terms of knowledge representation, adaptability, optimality, and processing speed for different real-world optimization problems. Focusing on the practical implementation of CI techniques, this book: Discusses the role of CI paradigms in engineering applications such as unit commitment and economic load dispatch, harmonic reduction, load frequency control and automatic voltage regulation, job shop scheduling, multidepot vehicle routing, and digital image watermarking Explains the impact of CI on power systems, control systems, industrial automation, and image processing through the above-mentioned applications Shows how to apply CI algorithms to constraint-based optimization problems using MATLAB® m-files and Simulink® models Includes experimental analyses and results of test systems Computational Intelligence Paradigms for Optimization Problems Using MATLAB®/ Simulink® provides a valuable reference for industry professionals and advanced undergraduate, postgraduate, and research students.
Computational Intelligence Paradigms in Economic and Financial Decision Making (Intelligent Systems Reference Library #99)
by Marina RestaThe book focuses on a set of cutting-edge research techniques, highlighting the potential of soft computing tools in the analysis of economic and financial phenomena and in providing support for the decision-making process. In the first part the textbook presents a comprehensive and self-contained introduction to the field of self-organizing maps, elastic maps and social network analysis tools and provides necessary background material on the topic, including a discussion of more recent developments in the field. In the second part the focus is on practical applications, with particular attention paid to budgeting problems, market simulations, and decision-making processes, and on how such problems can be effectively managed by developing proper methods to automatically detect certain patterns. The book offers a valuable resource for both students and practitioners with an introductory-level college math background.
Computational Intelligence Paradigms: Theory & Applications using MATLAB
by S. Sumathi Surekha PaneerselvamOffering a wide range of programming examples implemented in MATLAB, Computational Intelligence Paradigms: Theory and Applications Using MATLAB presents theoretical concepts and a general framework for computational intelligence (CI) approaches, including artificial neural networks, fuzzy systems, evolutionary computation, genetic algorithms and pr
Computational Intelligence Techniques and Their Applications to Software Engineering Problems (Computational Intelligence Techniques)
by Vishal Jain Sarika Jain Ankita Bansal Abha Jain Ankur ChoudharyComputational Intelligence Techniques and Their Applications to Software Engineering Problems focuses on computational intelligence approaches as applicable in varied areas of software engineering such as software requirement prioritization, cost estimation, reliability assessment, defect prediction, maintainability and quality prediction, size estimation, vulnerability prediction, test case selection and prioritization, and much more. The concepts of expert systems, case-based reasoning, fuzzy logic, genetic algorithms, swarm computing, and rough sets are introduced with their applications in software engineering. The field of knowledge discovery is explored using neural networks and data mining techniques by determining the underlying and hidden patterns in software data sets. Aimed at graduate students and researchers in computer science engineering, software engineering, information technology, this book: Covers various aspects of in-depth solutions of software engineering problems using computational intelligence techniques Discusses the latest evolutionary approaches to preliminary theory of different solve optimization problems under software engineering domain Covers heuristic as well as meta-heuristic algorithms designed to provide better and optimized solutions Illustrates applications including software requirement prioritization, software cost estimation, reliability assessment, software defect prediction, and more Highlights swarm intelligence-based optimization solutions for software testing and reliability problems
Computational Intelligence Techniques for Comparative Genomics: Dedicated to Prof. Allam Appa Rao on the Occasion of His 65th Birthday (SpringerBriefs in Applied Sciences and Technology)
by Vinit Kumar Gunjan Naresh Babu MuppalaneniThis Brief highlights Informatics and related techniques to Computer Science Professionals, Engineers, Medical Doctors, Bioinformatics researchers and other interdisciplinary researchers. Chapters include the Bioinformatics of Diabetes and several computational algorithms and statistical analysis approach to effectively study the disorders and possible causes along with medical applications.
Computational Intelligence Techniques for Trading and Investment (Routledge Advances in Experimental and Computable Economics #6)
by Konstantinos Theofilatos Christian Dunis Spiros Likothanassis Andreas Karathanasopoulos Georgios SermpinisComputational intelligence, a sub-branch of artificial intelligence, is a field which draws on the natural world and adaptive mechanisms in order to study behaviour in changing complex environments. This book provides an interdisciplinary view of current technological advances and challenges concerning the application of computational intelligence techniques to financial time-series forecasting, trading and investment. The book is divided into five parts. The first part introduces the most important computational intelligence and financial trading concepts, while also presenting the most important methodologies from these different domains. The second part is devoted to the application of traditional computational intelligence techniques to the fields of financial forecasting and trading, and the third part explores the applications of artificial neural networks in these domains. The fourth part delves into novel evolutionary-based hybrid methodologies for trading and portfolio management, while the fifth part presents the applications of advanced computational intelligence modelling techniques in financial forecasting and trading. This volume will be useful for graduate and postgraduate students of finance, computational finance, financial engineering and computer science. Practitioners, traders and financial analysts will also benefit from this book.