Soft Computing In Machine Learning
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Soft Computing And Machine Learning
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Author : Mohd Anas Wajid
language : en
Publisher: CRC Press
Release Date : 2025-04-28
Soft Computing And Machine Learning written by Mohd Anas Wajid and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-28 with Computers categories.
This reference text covers the theory and applications of soft computing and machine learning and presents readers with the intelligent fuzzy and neutrosophic rules that require situations where classical modeling approaches cannot be utilized, such as when there is incomplete, unclear, or imprecise information at hand or inadequate data. It further illustrates topics such as image processing, and power system analysis. This book: Discusses soft computing techniques including fuzzy Logic, rough sets, neutrosophic sets, neural networks, generative adversarial networks, and evolutionary computation Examines novel and contemporary advances in the fields of soft computing, fuzzy computing, neutrosophic computing, and machine learning systems, as well as their applications in real life Serves as a comprehensive reference for applying machine learning and neutrosophic sets in real-world applications such as smart cities, healthcare, and the Internet of Things Covers topics such as image processing, bioinformatics, natural language processing, supply chain management, and cybernetics Illustrates classification of neutrosophic machine learning, neutrosophic reinforcement learning, and applications of neutrosophic machine learning in emerging industries The text is written for senior undergraduate students, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, and information technology.
Soft Computing In Machine Learning
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Author :
language : en
Publisher:
Release Date : 2018-05
Soft Computing In Machine Learning written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05 with categories.
Soft Computing (SC) represents a significant paradigm shift in the aims of computing, which reflects the fact that the human mind, unlike present day computers, possesses a remarkable ability to store and process information which is pervasively imprecise, uncertain and lacking in categoricity. Soft Computing (SC) is an emerging field that consists of complementary elements of fuzzy logic, neural computing, evolutionary computation, machine learning and probabilistic reasoning. Due to their strong learning and cognitive ability and good tolerance of uncertainty and imprecision, soft computing techniques have found wide applications. The volume of data being produced is increasing at an exponential rate due to our unprecedented capacity to generate, capture and share vast amounts of data. In this context, Machine Learning (ML) algorithms can be used to extract information from these large volumes of data. However, these algorithms are computationally expensive.Soft Computing in Machine Learning deals with cutting-edge coverage dealing with an extensive volume of data, to teach machines and to improve decision making models. Hence, ML algorithms often demand prohibitive computational resources when facing large volumes of data. Therefore, the scientific breakthroughs of the future will undoubtedly be powered by advanced computing capabilities that will allow researchers to manipulate and explore massive datasets.This book aims to provide investigators in the areas of information systems, engineering, computer science, statistics and management, with an insightful source for the role of soft computing in machine learning. As well, social sciences, psychology, medicine, genetics, and other fields that are interested in solving intricate problems can much benefit from this book. The book can also serve as a beneficial tool for advanced undergraduate students in data mining and machine learning. It may be particularly interested for practitioners and researchers in the descriptions of real-world data mining projects performed with soft-computing.
Advances In Soft Computing And Machine Learning In Image Processing
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Author : Aboul Ella Hassanien
language : en
Publisher: Springer
Release Date : 2017-10-13
Advances In Soft Computing And Machine Learning In Image Processing written by Aboul Ella Hassanien and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-13 with Technology & Engineering categories.
This book is a collection of the latest applications of methods from soft computing and machine learning in image processing. It explores different areas ranging from image segmentation to the object recognition using complex approaches, and includes the theory of the methodologies used to provide an overview of the application of these tools in image processing. The material has been compiled from a scientific perspective, and the book is primarily intended for undergraduate and postgraduate science, engineering, and computational mathematics students. It can also be used for courses on artificial intelligence, advanced image processing, and computational intelligence, and is a valuable resource for researchers in the evolutionary computation, artificial intelligence and image processing communities.
Application Of Soft Computing Machine Learning Deep Learning And Optimizations In Geoengineering And Geoscience
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Author : Wengang Zhang
language : en
Publisher: Springer Nature
Release Date : 2021-10-12
Application Of Soft Computing Machine Learning Deep Learning And Optimizations In Geoengineering And Geoscience written by Wengang Zhang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-12 with Science categories.
This book summarizes the application of soft computing techniques, machine learning approaches, deep learning algorithms and optimization techniques in geoengineering including tunnelling, excavation, pipelines, etc. and geoscience including the geohazards, rock and soil properties, etc. The book features state-of-the-art studies on use of SC,ML,DL and optimizations in Geoengineering and Geoscience. Considering these points and understanding, this book will be compiled with highly focussed chapters that will discuss the application of SC,ML,DL and optimizations in Geoengineering and Geoscience. Target audience: (1) Students of UG, PG, and Research Scholars: Several applications of SC,ML,DL and optimizations in Geoengineering and Geoscience can help students to enhance their knowledge in this domain. (2) Industry Personnel and Practitioner: Practitioners from different fields can be able to implement standard and advanced SC,ML,DL and optimizations for solving critical problems of civil engineering.
Applied Soft Computing
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Author : Samarjeet Borah
language : en
Publisher: CRC Press
Release Date : 2022-02-02
Applied Soft Computing written by Samarjeet Borah and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-02 with Computers categories.
This new volume explores a variety of modern techniques that deal with estimated models and give resolutions to complex real-life issues. Soft computing has played a crucial role not only with theoretical paradigms but is also popular for its pivotal role for designing a large variety of expert systems and artificial intelligence-based applications. Involving the concepts and practices of soft computing in conjunction with other frontier research domains, this book begins with the basics and goes on to explore a variety of modern applications of soft computing in areas such as approximate reasoning, artificial neural networks, Bayesian networks, big data analytics, bioinformatics, cloud computing, control systems, data mining, functional approximation, fuzzy logic, genetic and evolutionary algorithms, hybrid models, machine learning, metaheuristics, neuro fuzzy system, optimization, randomized searches, and swarm intelligence. This book will be helpful to a wide range of readers who wish to learn applications of soft computing approaches. It will be useful for academicians, researchers, students, and machine learning experts who use soft computing techniques and algorithms to develop cutting-edge artificial intelligence-based applications.
Soft Computing Techniques In Engineering Health Mathematical And Social Sciences
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Author : Pradip Debnath
language : en
Publisher: CRC Press
Release Date : 2021-07-15
Soft Computing Techniques In Engineering Health Mathematical And Social Sciences written by Pradip Debnath and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-15 with Computers categories.
Soft computing techniques are no longer limited to the arena of computer science. The discipline has an exponentially growing demand in other branches of science and engineering and even into health and social science. This book contains theory and applications of soft computing in engineering, health, and social and applied sciences. Different soft computing techniques such as artificial neural networks, fuzzy systems, evolutionary algorithms and hybrid systems are discussed. It also contains important chapters in machine learning and clustering. This book presents a survey of the existing knowledge and also the current state of art development through original new contributions from the researchers. This book may be used as a one-stop reference book for a broad range of readers worldwide interested in soft computing. In each chapter, the preliminaries have been presented first and then the advanced discussion takes place. Learners and researchers from a wide variety of backgrounds will find several useful tools and techniques to develop their soft computing skills. This book is meant for graduate students, faculty and researchers willing to expand their knowledge in any branch of soft computing. The readers of this book will require minimum prerequisites of undergraduate studies in computation and mathematics.
New Learning Paradigms In Soft Computing
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Author : Lakhmi C. Jain
language : en
Publisher: Springer Science & Business Media
Release Date : 2002
New Learning Paradigms In Soft Computing written by Lakhmi C. Jain and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Computers categories.
Learning is a key issue in the analysis and design of all kinds of intelligent systems. In recent time many new paradigms of automated (machine) learning have been proposed in the literature. Soft computing, that has proved to be an effective and efficient tool in so many areas of science and technology, seems to offer new qualities in the realm of machine learning too. The purpose of this volume is to present some new learning paradigms that have been triggered, or at least strongly influenced by soft computing tools and techniques, mainly related to neural networks, fuzzy logic, rough sets, and evolutionary computations.
Machine Learning And Soft Computing
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Author : Letian Huang
language : en
Publisher: Springer Nature
Release Date : 2025-06-24
Machine Learning And Soft Computing written by Letian Huang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-24 with Mathematics categories.
This two part-volume CCIS constitutes the refereed proceedings of 9th International Conference, ICMLSC 2025, in Tokyo, Japan in January 24–26, 2025. The 39 full papers and 13 short papers included in this book were carefully reviewed and selected from 121 submissions. They follow the topical sections as below: Part I : Multimodal Data Analysis and Model Optimization; Basic Theories of Machine Learning and Emerging Application Technologies; and Intelligent Recommendation System Design and Privacy Security. Part II : Deep Learning Models and High-performance Computing; Data-driven Complex System Modeling and Intelligent Optimization Algorithms; and Image Analysis and Processing Methods based on AI.
Advances In Soft Computing
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Author : Ildar Batyrshin
language : en
Publisher: Springer
Release Date : 2019-01-02
Advances In Soft Computing written by Ildar Batyrshin and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-02 with Computers categories.
The two-volume set LNAI 11288 and 11289 constitutes the proceedings of the 17th Mexican International Conference on Artificial Intelligence, MICAI 2018, held in Guadalajara, Mexico, in October 2018. The total of 62 papers presented in these two volumes was carefully reviewed and selected from 149 submissions. The contributions are organized in topical as follows: Part I: evolutionary and nature-inspired intelligence; machine learning; fuzzy logic and uncertainty management. Part II: knowledge representation, reasoning, and optimization; natural language processing; and robotics and computer vision.
Soft Computing And Machine Learning In Dam Engineering
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Author : M Amin Hariri-Ardebili
language : en
Publisher: Mdpi AG
Release Date : 2023-05-10
Soft Computing And Machine Learning In Dam Engineering written by M Amin Hariri-Ardebili and has been published by Mdpi AG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-10 with Technology & Engineering categories.
"Soft Computing and Machine Learning in Dam Engineering" is a comprehensive, edited Special Issue that explores the latest advances in the application of soft computing and machine learning techniques to dam engineering. This reprint covers a range of topics, including dam design, construction, monitoring, and maintenance, and provides readers with a deep understanding of the theoretical foundations and practical applications of these techniques. Featuring contributions from leading experts in the field, the reprint presents a collection of 11 papers that offer insights into state-of-the-art approaches in dam engineering. The chapters cover topics such as fuzzy logic, genetic algorithms, artificial neural networks, and support vector machines, and provide practical examples of how these techniques can be applied to solve real-world dam engineering problems. Whether you are a researcher, engineer, or student in the field of dam engineering, "Soft Computing and Machine Learning in Dam Engineering" provides a valuable resource for staying up-to-date with the latest techniques and approaches in the field.