Download or read book Mathematical Modeling Computational Intelligence Techniques and Renewable Energy written by Manoj Sahni and published by Springer Nature. This book was released on 2021-02-28 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Mathematical Modeling Computational Intelligence Techniques and Renewable Energy written by Manoj Sahni and published by Springer Nature. This book was released on 2021-12-11 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents new knowledge and recent developments in all aspects of computational techniques, mathematical modeling, energy systems, and applications of fuzzy sets and intelligent computing. The book is a collection of best selected research papers presented at the Second International Conference on “Mathematical Modeling, Computational Intelligence Techniques and Renewable Energy (MMCITRE 2021),” organized by the Department of Mathematics, Pandit Deendayal Petroleum University, in association with Forum for Interdisciplinary Mathematics. The book provides innovative works of researchers, academicians, and students in the area of interdisciplinary mathematics, statistics, computational intelligence, and renewable energy.

Download or read book Mathematical Modelling and Computational Intelligence Techniques written by P. Balasubramaniam and published by Springer Nature. This book was released on 2022-01-13 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Mathematical Modeling and Computational Intelligence in Engineering Applications written by Antônio José da Silva Neto and published by Springer. This book was released on 2016-08-12 with total page 179 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Applied Mathematics and Computational Intelligence written by Anna M. Gil-Lafuente and published by Springer. This book was released on 2018-03-06 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers selected papers presented at the conference of the Forum for Interdisciplinary Mathematics (FIM), held at Palau Macaya, Barcelona, on 18 to 20 November, 2015. The event was co-organized by the University of Barcelona (Spain), the Spanish Royal Academy of Economic and Financial Sciences (Spain) and the Forum for Interdisciplinary Mathematics (India). This instalment of the conference was presented with the title “Applied Mathematics and Computational Intelligence” and particularly focused on the use of Mathematics and Computational Intelligence techniques in a diverse range of scientific disciplines, as well as their applications in real-world problems. The book presents thirty peer-reviewed research papers, organised into four topical sections: on Mathematical Foundations; Computational Intelligence and Optimization Techniques; Modelling and Simulation Techniques; and Applications in Business and Engineering. This book will be of great interest to anyone working in the area of applied mathematics and computational intelligence and will be especially useful for scientists and graduate students pursuing research in these fields.

Download or read book Mathematical Modeling Computational Intelligence Techniques and Renewable Energy written by Manoj Sahni and published by Springer Nature. This book was released on 2023-05-08 with total page 474 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is a collection of best selected research papers presented at the Third International Conference on “Mathematical Modeling, Computational Intelligence Techniques and Renewable Energy (MMCITRE 2022),” organized by the University of Technology Sydney, Australia, in association with the Department of Mathematics, Pandit Deendayal Energy University, India, and Forum for Interdisciplinary Mathematics. 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 provides innovative works of researchers, academicians and students in the area of interdisciplinary mathematics, statistics, computational intelligence and renewable energy.

Download or read book Interactions Between Computational Intelligence and Mathematics written by László T. Kóczy and published by Springer. This book was released on 2018-03-10 with total page 119 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent research in the field of interaction between computational intelligence and mathematics, ranging from theory to applications. Computational intelligence, or soft computing consists of various bio-inspired methods, especially fuzzy systems, artificial neural networks, evolutionary and memetic algorithms. These research areas were initiated by professionals in various applied fields, such as engineers, economists, and financial and medical experts. Although computational intelligence offered solutions (at least quasi-optimal solutions) for problems with high complexity, vague and undeterministic features, initially little attention was paid to the mathematical models and analysis of the methods successfully applied. A typical example is the extremely successful Mamdani-algorithm, and its modifications and extensions, applied since the mid-1970s, where the first analysis of the simplest cases, showing why this algorithm was so efficient and stable, was not given until the early 1990s. Since the mid-2000s, the authors have organized international conferences annually to focus on the mathematical methodological issues in connection with computational intelligence approaches. These conferences have attracted a large number of submissions with a wide scope of topics and quality. The editors selected several high-quality papers and approached the authors to submit an essentially extended and improved book chapter based on the lectures.This volume is the first contributed book on the subject.

Download or read book Computational Intelligence and Mathematics for Tackling Complex Problems 4 written by María Eugenia Cornejo and published by Springer Nature. This book was released on 2022-09-20 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: The recent book of the series continues the collection of articles dealing with the important and efficient combination of traditional and novel mathematical approaches with various computational intelligence techniques, with a stress of fuzzy systems, and fuzzy logic. Complex systems are theoretically intractable, as the need of time and space resources (e.g., computer capacity) exceed any implementable extent. How is it possible that in the practice, such problems are usually manageable with an acceptable quality by human experts? They apply expert domain knowledge and various methods of approximate modeling and corresponding algorithms. Computational intelligence is the mathematical tool box that collects techniques which are able to model such human interaction, while (new) mathematical approaches are developed and used everywhere where the complexity of the sub-task allows it. The innovative approaches in this book give answer to many questions on how to solve “unsolvable” problems.

Download or read book Computational Statistical Methodologies and Modeling for Artificial Intelligence written by Priyanka Harjule and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers computational statistics-based approaches for Artificial Intelligence. The aim of this book is to provide comprehensive coverage of the fundamentals through the applications of the different kinds of mathematical modelling and statistical techniques and describing their applications in different Artificial Intelligence systems. The primary users of this book will include researchers, academicians, postgraduate students, and specialists in the areas of data science, mathematical modelling, and Artificial Intelligence. It will also serve as a valuable resource for many others in the fields of electrical, computer, and optical engineering. The key features of this book are: Presents development of several real-world problem applications and experimental research in the field of computational statistics and mathematical modelling for Artificial Intelligence Examines the evolution of fundamental research into industrialized research and the transformation of applied investigation into real-time applications Examines the applications involving analytical and statistical solutions, and provides foundational and advanced concepts for beginners and industry professionals Provides a dynamic perspective to the concept of computational statistics for analysis of data and applications in intelligent systems with an objective of ensuring sustainability issues for ease of different stakeholders in various fields Integrates recent methodologies and challenges by employing mathematical modeling and statistical techniques for Artificial Intelligence

Download or read book Applied Computational Intelligence and Mathematical Methods written by Radek Silhavy and published by Springer. This book was released on 2017-09-04 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book discusses real-world problems and exploratory research in computational intelligence and mathematical models. It brings new approaches and methods to real-world problems and exploratory research that describes novel approaches in the mathematical methods, computational intelligence methods and software engineering in the scope of the intelligent systems. This book constitutes the refereed proceedings of the Computational Methods in Systems and Software 2017, a conference that provided an international forum for the discussion of the latest high-quality research results in all areas related to computational methods, statistics, cybernetics and software engineering.

Download or read book Mathematical Modeling for Intelligent Systems written by Mukesh Kumar Awasthi and published by CRC Press. This book was released on 2022-07-29 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical Modeling for Intelligent Systems: Theory, Methods, and Simulation aims to provide a reference for the applications of mathematical modeling using intelligent techniques in various unique industry problems in the era of Industry 4.0. Providing a thorough introduction to the field of soft-computing techniques, this book covers every major technique in artificial intelligence in a clear and practical style. It also highlights current research and applications, addresses issues encountered in the development of applied systems, and describes a wide range of intelligent systems techniques, including neural networks, fuzzy logic, evolutionary strategy, and genetic algorithms. This book demonstrates concepts through simulation examples and practical experimental results. Key Features: • Offers a well-balanced mathematical analysis of modeling physical systems • Summarizes basic principles in differential geometry and convex analysis as needed • Covers a wide range of industrial and social applications and bridges the gap between core theory and costly experiments through simulations and modeling • Focuses on manifold ranging from stability of fluid flows, nanofluids, drug delivery, and security of image data to pandemic modeling, etc. This book is primarily aimed at advanced undergraduates and postgraduate students studying computer science, mathematics, and statistics. Researchers and professionals will also find this book useful.

Download or read book Computational Intelligence for Modelling and Prediction written by Saman K. Halgamuge and published by Springer Science & Business Media. This book was released on 2005-09-02 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: The application of Computational Intelligence in emerging research areas such as Granular Computing, Mechatronics, and Bioinformatics shows its usefulness often emphasized by Prof Lotfi Zadeh, the inventor of fuzzy logic and many others. This book contains recent advances in Computational Intelligence methods for modeling, optimization and prediction and covers a large number of applications. The book presents new Computational Intelligence theory and methods for modeling and prediction. The range of the various applications is captured with 5 chapters in image processing, 2 chapters in audio processing, 3 chapters in commerce and finance, 2 chapters in communication networks and 6 chapters containing other applications.

Download or read book Finite Element Model Updating Using Computational Intelligence Techniques written by Tshilidzi Marwala and published by Springer Science & Business Media. This book was released on 2010-06-04 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: FEM updating allows FEMs to be tuned better to reflect measured data. It can be conducted using two different statistical frameworks: the maximum likelihood approach and Bayesian approaches. This book applies both strategies to the field of structural mechanics, using vibration data. Computational intelligence techniques including: multi-layer perceptron neural networks; particle swarm and GA-based optimization methods; simulated annealing; response surface methods; and expectation maximization algorithms, are proposed to facilitate the updating process. Based on these methods, the most appropriate updated FEM is selected, a problem that traditional FEM updating has not addressed. This is found to incorporate engineering judgment into finite elements through the formulations of prior distributions. Case studies, demonstrating the principles test the viability of the approaches, and. by critically analysing the state of the art in FEM updating, this book identifies new research directions.

Download or read book Computational Statistics and Mathematical Modeling Methods in Intelligent Systems written by Radek Silhavy and published by Springer Nature. This book was released on 2019-09-19 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents real-world problems and exploratory research in computational statistics, mathematical modeling, artificial intelligence and software engineering in the context of the intelligent systems. This book constitutes the refereed proceedings of the 3rd Computational Methods in Systems and Software 2019 (CoMeSySo 2019), a groundbreaking online conference that provides an international forum for discussing the latest high-quality research results.

Download or read book Constraint Handling in Metaheuristics and Applications written by Anand J. Kulkarni and published by Springer Nature. This book was released on 2021-04-12 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to discuss the core and underlying principles and analysis of the different constraint handling approaches. The main emphasis of the book is on providing an enriched literature on mathematical modelling of the test as well as real-world problems with constraints, and further development of generalized constraint handling techniques. These techniques may be incorporated in suitable metaheuristics providing a solid optimized solution to the problems and applications being addressed. The book comprises original contributions with an aim to develop and discuss generalized constraint handling approaches/techniques for the metaheuristics and/or the applications being addressed. A variety of novel as well as modified and hybridized techniques have been discussed in the book. The conceptual as well as the mathematical level in all the chapters is well within the grasp of the scientists as well as the undergraduate and graduate students from the engineering and computer science streams. The reader is encouraged to have basic knowledge of probability and mathematical analysis and optimization. The book also provides critical review of the contemporary constraint handling approaches. The contributions of the book may further help to explore new avenues leading towards multidisciplinary research discussions. This book is a complete reference for engineers, scientists, and students studying/working in the optimization, artificial intelligence (AI), or computational intelligence arena.

Download or read book Computational Intelligence and Mathematics for Tackling Complex Problems written by László T Kóczy and published by Springer. This book was released on 2019-05-02 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book combines computational intelligence and mathematics to solve theoretical and real-world problems. The real challenges of engineering and other applied sciences, e.g. economics and management, the social sciences, etc., and even everyday life, are increasingly raising complex problems – both in the usual sense, but also in the mathematical and theoretical computer science sense, which is referred to as intractability. Finding exact solutions to the latest problems in mathematics is impossible, and it has been also shown that no further technical advance will ever make it possible to find general and exact solutions to such complex problems. Rather, the goal is to find solutions that are “good enough” or “acceptably accurate,” including models and corresponding algorithms, which is most often achieved by combining traditional mathematical techniques and computational intelligence tools, such as fuzzy systems, evolutionary and memetic algorithms, and artificial neural networks. Consequently, international funding programs, such as the European Commission’s current framework program for research and innovation (Horizon 2020), and the preliminary research team building COST Actions, are devoted to developing new instruments for tackling the challenges that we face in the current technological age. And it goes without saying that research topics concerning the interactions between computational intelligence and traditional mathematics play a key role in overcoming the obstacles associated with the intractability of complex problems. In this book, mathematicians, engineers, and other scientists highlight novel methodological results connecting these two main research areas, and focusing on solving real-life problems.

Download or read book Mathematical Methods in Artificial Intelligence written by Edward A. Bender and published by Wiley-IEEE Computer Society Press. This book was released on 1996-02-10 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical Methods in Artificial Intelligence introduces the student to the important mathematical foundations and tools in AI and describes their applications to the design of AI algorithms. This useful text presents an introductory AI course based on the most important mathematics and its applications. It focuses on important topics that are proven useful in AI and involve the most broadly applicable mathematics. The book explores AI from three different viewpoints: goals, methods or tools, and achievements and failures. Its goals of reasoning, planning, learning, or language understanding and use are centered around the expert system idea. The tools of AI are presented in terms of what can be incorporated in the data structures. The book looks into the concepts and tools of limited structure, mathematical logic, logic-like representation, numerical information, and nonsymbolic structures. The text emphasizes the main mathematical tools for representing and manipulating knowledge symbolically. These are various forms of logic for qualitative knowledge, and probability and related concepts for quantitative knowledge. The main tools for manipulating knowledge nonsymbolically, as neural nets, are optimization methods and statistics. This material is covered in the text by topics such as trees and search, classical mathematical logic, and uncertainty and reasoning. A solutions diskette is available, please call for more information.