Machine Learning And Soft Computing
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Machine Intelligence And Soft Computing
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Author : Debnath Bhattacharyya
language : en
Publisher:
Release Date : 2021
Machine Intelligence And Soft Computing written by Debnath Bhattacharyya and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
This book gathers selected papers presented at the International Conference on Machine Intelligence and Soft Computing (ICMISC 2020), held jointly by Vignan's Institute of Information Technology, Visakhapatnam, India and VFSTR Deemed to be University, Guntur, AP, India during 03-04 September 2020. Topics covered in the book include the artificial neural networks and fuzzy logic, cloud computing, evolutionary algorithms and computation, machine learning, metaheuristics and swarm intelligence, neuro-fuzzy system, soft computing and decision support systems, soft computing applications in actuarial science, soft computing for database deadlock resolution, soft computing methods in engineering, and support vector machine.
Learning And Soft Computing
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Author : Vojislav Kecman
language : en
Publisher: MIT Press
Release Date : 2001
Learning And Soft Computing written by Vojislav Kecman and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Computers categories.
This textbook provides a thorough introduction to the field of learning from experimental data and soft computing. Support vector machines (SVM) and neural networks (NN) are the mathematical structures, or models, that underlie learning, while fuzzy logic systems (FLS) enable us to embed structured human knowledge into workable algorithms. The book assumes that it is not only useful, but necessary, to treat SVM, NN, and FLS as parts of a connected whole. Throughout, the theory and algorithms are illustrated by practical examples, as well as by problem sets and simulated experiments. This approach enables the reader to develop SVM, NN, and FLS in addition to understanding them. The book also presents three case studies: on NN-based control, financial time series analysis, and computer graphics. A solutions manual and all of the MATLAB programs needed for the simulated experiments are available.
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.
Neuro Fuzzy And Soft Computing
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Author : Jyh-Shing Roger Jang
language : en
Publisher: Pearson Education
Release Date : 1997
Neuro Fuzzy And Soft Computing written by Jyh-Shing Roger Jang and has been published by Pearson Education this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with Computers categories.
Neuro-Fuzzy and Soft Computing provides the first comprehensive treatment of the constituent methodologies underlying neuro-fuzzy and soft computing, an evolving branch of computational intelligence. The constituent methodologies include fuzzy set theory, neural networks, data clustering techniques, and several stochastic optimization methods that do not require gradient information. In particular, the authors put equal emphasis on theoretical aspects of covered methodologies, as well as empirical observations and verifications of various applications in practice. The book is well suited for use as a text for courses on computational intelligence and as a single reference source for this emerging field. To help readers understand the material the presentation includes more than 50 examples, more than 150 exercises, over 300 illustrations, and more than 150 Matlab scripts. In addition, Matlab is utilized to visualize the processes of fuzzy reasoning, neural-network learning, neuro-fuzzy integration and training, and gradient-free optimization (such as genetic algorithms, simulated annealing, random search, and downhill Simplex method). The presentation also makes use of SIMULINK for neuro-fuzzy control system simulations. All Matlab scripts used in the book are available on the free companion software disk that may be ordered by using the enclosed reply card. The book also contains an "Internet Resource Page" to point the reader to on-line neuro-fuzzy and soft computing home pages, publications, public-domain software, research institutes, news groups, etc. All the HTTP and FTP addresses are available as a bookmark file on the companion software disk.
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.
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.
Advances On Smart And Soft Computing
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Author : Faisal Saeed
language : en
Publisher: Springer Nature
Release Date : 2020-10-19
Advances On Smart And Soft Computing written by Faisal Saeed and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-19 with Technology & Engineering categories.
This book gathers high-quality papers presented at the First International Conference of Advanced Computing and Informatics (ICACIn 2020), held in Casablanca, Morocco, on April 12–13, 2020. It covers a range of topics, including artificial intelligence technologies and applications, big data analytics, smart computing, smart cities, Internet of things (IoT), data communication, cloud computing, machine learning algorithms, data stream management and analytics, deep learning, data mining applications, information retrieval, cloud computing platforms, parallel processing, natural language processing, predictive analytics, knowledge management approaches, information security, security in IoT, big data and cloud computing, high-performance computing and computational informatics.
New Learning Paradigms In Soft Computing
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Author : Lakhmi C. Jain
language : en
Publisher: Physica
Release Date : 2013-06-05
New Learning Paradigms In Soft Computing written by Lakhmi C. Jain and has been published by Physica this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-05 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.
Neural Networks In A Softcomputing Framework
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Author : Ke-Lin Du
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-08-02
Neural Networks In A Softcomputing Framework written by Ke-Lin Du 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 2006-08-02 with Computers categories.
Conventional model-based data processing methods are computationally expensive and require experts’ knowledge for the modelling of a system. Neural networks are a model-free, adaptive, parallel-processing solution. This textbook provides a powerful and universal paradigm for information processing; it reviews the most popular neural-network methods and their associated techniques. Each chapter has a systematic survey of each neural-network model. Computational intelligence topics like fuzzy logic and genetic algorithms (tools for neural-network learning) are introduced. Array signal processing problems are used to show the applications of each model. This is an ideal textbook for graduate students and researchers; as well as introducing the basics, the exhaustive list of references included will aid their future research. It is also a valuable reference for scientists and practitioners working in pattern recognition, signal processing, speech and image processing, data analysis and A.I.
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.