Applied Analysis Optimization And Soft Computing
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Author | : Tanmoy Som |
Publisher | : Springer Nature |
Total Pages | : 425 |
Release | : 2023-06-10 |
Genre | : Mathematics |
ISBN | : 9819905974 |
This book contains select contributions presented at the International Conference on Nonlinear Applied Analysis and Optimization (ICNAAO-2021), held at the Department of Mathematics Sciences, Indian Institute of Technology (BHU) Varanasi, India, from 21–23 December 2021. The book discusses topics in the areas of nonlinear analysis, fixed point theory, dynamical systems, optimization, fractals, applications to differential/integral equations, signal and image processing, and soft computing, and exposes the young talents with the newer dimensions in these areas with their practical approaches and to tackle the real-life problems in engineering, medical and social sciences. Scientists from the U.S.A., Austria, France, Mexico, Romania, and India have contributed their research. All the submissions are peer reviewed by experts in their fields.
Author | : Tanmoy Som |
Publisher | : |
Total Pages | : 0 |
Release | : 2023 |
Genre | : |
ISBN | : 9789819905980 |
This book contains select contributions presented at the International Conference on Nonlinear Applied Analysis and Optimization (ICNAAO-2021), held at the Department of Mathematics, Indian Institute of Technology (BHU) Varanasi, India, from 21-23 December 2021. The book discusses topics in the areas of nonlinear analysis, fixed point theory, dynamical systems, optimization, fractals, applications to differential/integral equations, signal and image processing, and soft computing, and exposes the young talents with the newer dimensions in these areas with their practical approaches and to tackle the real-life problems in engineering, medical and social sciences. Scientists from the U.S.A., Austria, France, Mexico, Romania, and India have contributed their research. All the submissions are peer reviewed by experts in their fields.
Author | : Saxena, Pratiksha |
Publisher | : IGI Global |
Total Pages | : 424 |
Release | : 2016-03-01 |
Genre | : Mathematics |
ISBN | : 1466698861 |
Optimization techniques have developed into a modern-day solution for real-world problems in various industries. As a way to improve performance and handle issues of uncertainty, optimization research becomes a topic of special interest across disciplines. Problem Solving and Uncertainty Modeling through Optimization and Soft Computing Applications presents the latest research trends and developments in the area of applied optimization methodologies and soft computing techniques for solving complex problems. Taking a multi-disciplinary approach, this critical publication is an essential reference source for engineers, managers, researchers, and post-graduate students.
Author | : Hemen Dutta |
Publisher | : Springer Nature |
Total Pages | : 433 |
Release | : 2023-07-20 |
Genre | : Technology & Engineering |
ISBN | : 9811980543 |
The volume contains original research papers as the Proceedings of the International Conference on Applied Nonlinear Analysis and Soft Computing (ANASC 2020), held at Gauhati University, Guwahati, India, on 22-23 December, 2020. It focuses on current research topics in applied analysis including nonlinearity, soft computing and related areas. It primarily includes topics related to pattern recognition, reaction-diffusion problem, decision making problems, inventory model, predator-prey model, logistic models, wave problems, problems in Magnetohydrodynamics, cosmological model, harmonic functions, graphs, shapes, etc. Researchers, educators, scientist and professionals interested in recent developments in applied analysis including nonlinearity aspects and soft computing should be benefited from this volume.
Author | : Shandilya, Shishir K. |
Publisher | : IGI Global |
Total Pages | : 649 |
Release | : 2017-03-10 |
Genre | : Computers |
ISBN | : 1522521291 |
Soft computing and nature-inspired computing both play a significant role in developing a better understanding to machine learning. When studied together, they can offer new perspectives on the learning process of machines. The Handbook of Research on Soft Computing and Nature-Inspired Algorithms is an essential source for the latest scholarly research on applications of nature-inspired computing and soft computational systems. Featuring comprehensive coverage on a range of topics and perspectives such as swarm intelligence, speech recognition, and electromagnetic problem solving, this publication is ideally designed for students, researchers, scholars, professionals, and practitioners seeking current research on the advanced workings of intelligence in computing systems.
Author | : Patricia Melin |
Publisher | : Springer |
Total Pages | : 341 |
Release | : 2012-12-14 |
Genre | : Technology & Engineering |
ISBN | : 3642353231 |
Soft computing includes several intelligent computing paradigms, like fuzzy logic, neural networks, and bio-inspired optimization algorithms. This book describes the application of soft computing techniques to intelligent control, pattern recognition, and optimization problems. The book is organized in four main parts. The first part deals with nature-inspired optimization methods and their applications. Papers included in this part propose new models for achieving intelligent optimization in different application areas. The second part discusses hybrid intelligent systems for achieving control. Papers included in this part make use of nature-inspired techniques, like evolutionary algorithms, fuzzy logic and neural networks, for the optimal design of intelligent controllers for different kind of applications. Papers in the third part focus on intelligent techniques for pattern recognition and propose new methods to solve complex pattern recognition problems. The fourth part discusses new theoretical concepts and methods for the application of soft computing to many different areas, such as natural language processing, clustering and optimization.
Author | : S. Chakraverty |
Publisher | : Springer Nature |
Total Pages | : 264 |
Release | : 2021-11-01 |
Genre | : Technology & Engineering |
ISBN | : 9811647135 |
This book meets the present and future needs for the interaction between various science and technology/engineering areas on the one hand and different branches of soft computing on the other. Soft computing is the recent development about the computing methods which include fuzzy set theory/logic, evolutionary computation (EC), probabilistic reasoning, artificial neural networks, machine learning, expert systems, etc. Soft computing refers to a partnership of computational techniques in computer science, artificial intelligence, machine learning, and some other engineering disciplines, which attempt to study, model, and analyze complex problems from different interdisciplinary problems. This, as opposed to traditional computing, deals with approximate models and gives solutions to complex real-life problems. Unlike hard computing, soft computing is tolerant of imprecision, uncertainty, partial truth, and approximations. Interdisciplinary sciences include various challenging problems of science and engineering. Recent developments in soft computing are the bridge to handle different interdisciplinary science and engineering problems. In recent years, the correspondingly increased dialog between these disciplines has led to this new book. This is done, firstly, by encouraging the ways that soft computing may be applied in traditional areas, as well as point towards new and innovative areas of applications and secondly, by encouraging other scientific disciplines to engage in a dialog with the above computation algorithms outlining their problems to both access new methods as well as to suggest innovative developments within itself.
Author | : B. V. Babu |
Publisher | : Springer |
Total Pages | : 1529 |
Release | : 2014-07-08 |
Genre | : Technology & Engineering |
ISBN | : 8132216024 |
The present book is based on the research papers presented in the International Conference on Soft Computing for Problem Solving (SocProS 2012), held at JK Lakshmipat University, Jaipur, India. This book provides the latest developments in the area of soft computing and covers a variety of topics, including mathematical modeling, image processing, optimization, swarm intelligence, evolutionary algorithms, fuzzy logic, neural networks, forecasting, data mining, etc. The objective of the book is to familiarize the reader with the latest scientific developments that are taking place in various fields and the latest sophisticated problem solving tools that are being developed to deal with the complex and intricate problems that are otherwise difficult to solve by the usual and traditional methods. The book is directed to the researchers and scientists engaged in various fields of Science and Technology.
Author | : Saifullah Khalid |
Publisher | : Engineering Science Reference |
Total Pages | : 0 |
Release | : 2017-09-13 |
Genre | : Computational intelligence |
ISBN | : 9781522531296 |
Presents the latest scholarly research on the concepts, paradigms, and algorithms of computational intelligence and its constituent methodologies, such as evolutionary computation, neural networks, and fuzzy logic. This volume ncludes coverage on a broad range of topics and perspectives such as cloud computing, sampling in optimization, and swarm intelligence.
Author | : Xin-She Yang |
Publisher | : Academic Press |
Total Pages | : 312 |
Release | : 2020-09-09 |
Genre | : Science |
ISBN | : 0128219890 |
Nature-Inspired Optimization Algorithms, Second Edition provides an introduction to all major nature-inspired algorithms for optimization. The book's unified approach, balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with case studies to illustrate how these algorithms work. Topics include particle swarm optimization, ant and bee algorithms, simulated annealing, cuckoo search, firefly algorithm, bat algorithm, flower algorithm, harmony search, algorithm analysis, constraint handling, hybrid methods, parameter tuning and control, and multi-objective optimization. This book can serve as an introductory book for graduates, for lecturers in computer science, engineering and natural sciences, and as a source of inspiration for new applications. - Discusses and summarizes the latest developments in nature-inspired algorithms with comprehensive, timely literature - Provides a theoretical understanding and practical implementation hints - Presents a step-by-step introduction to each algorithm - Includes four new chapters covering mathematical foundations, techniques for solving discrete and combination optimization problems, data mining techniques and their links to optimization algorithms, and the latest deep learning techniques, background and various applications