Machine Learning And Mechanics Based Soft Computing Applications
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Machine Learning And Mechanics Based Soft Computing Applications
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Author : Thi Dieu Linh Nguyen
language : en
Publisher: Springer Nature
Release Date : 2023-03-01
Machine Learning And Mechanics Based Soft Computing Applications written by Thi Dieu Linh Nguyen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-01 with Technology & Engineering categories.
This book highlights recent advances in the area of machine learning and robotics-based soft computing applications. The book covers various artificial intelligence, machine learning, and mechanics, a mix of mechanical computational engineering work. The current computing era has a huge market/potential for machine learning, robotics, and soft computing techniques and their applications. With this in view, the book shares latest research and cutting-edge applications useful for professionals and researchers in these areas.
Applied Soft Computing
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Author : Samarjeet Borah
language : en
Publisher: CRC Press
Release Date : 2022-02-03
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 2022-02-03 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.
Handbook Of Research On Novel Soft Computing Intelligent Algorithms
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Author : Pandian Vasant
language : en
Publisher: IGI Global
Release Date : 2013-08-31
Handbook Of Research On Novel Soft Computing Intelligent Algorithms written by Pandian Vasant and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-08-31 with Technology & Engineering categories.
"This book explores emerging technologies and best practices designed to effectively address concerns inherent in properly optimizing advanced systems, demonstrating applications in areas such as bio-engineering, space exploration, industrial informatics, information security, and nuclear and renewable energies"--Provided by publisher.
Soft Computing In Interdisciplinary Sciences
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Author : S. Chakraverty
language : en
Publisher: Springer Nature
Release Date : 2021-11-01
Soft Computing In Interdisciplinary Sciences written by S. Chakraverty and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-01 with Technology & Engineering categories.
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.
Advances In Soft Computing Applications
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Author : Shristi Kharola
language : en
Publisher:
Release Date : 2023
Advances In Soft Computing Applications written by Shristi Kharola and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with COMPUTERS categories.
The proclivity of today’s technology to think like humans may be seen in new developing disciplines such as neural computing, fuzzy logic, evolutionary computation, machine learning, and probabilistic reasoning. These strategies are grouped together into one main technique known as "soft computing." This book discusses the most recent soft computing and fuzzy logic-based applications and innovations in industrial advancements, supply chain and logistics, system optimization, decision-making, artificial intelligence, smart systems, and other rapidly evolving technologies. In today’s competitive world, the book provides soft computing solutions to help companies overcome the obstacles posed by sophisticated decision-making systems.
Neural Networks And Soft Computing
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Author : Leszek Rutkowski
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-20
Neural Networks And Soft Computing written by Leszek Rutkowski 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 2013-03-20 with Computers categories.
This volume presents new trends and developments in soft computing techniques. Topics include: neural networks, fuzzy systems, evolutionary computation, knowledge discovery, rough sets, and hybrid methods. It also covers various applications of soft computing techniques in economics, mechanics, medicine, automatics and image processing. The book contains contributions from internationally recognized scientists, such as Zadeh, Bubnicki, Pawlak, Amari, Batyrshin, Hirota, Koczy, Kosinski, Novák, S.-Y. Lee, Pedrycz, Raudys, Setiono, Sincak, Strumillo, Takagi, Usui, Wilamowski and Zurada. An excellent overview of soft computing methods and their applications.
Soft Computing In Machine Learning
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Author : Sang-Yong Rhee
language : en
Publisher: Springer
Release Date : 2014-07-08
Soft Computing In Machine Learning written by Sang-Yong Rhee and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-08 with Technology & Engineering categories.
As users or consumers are now demanding smarter devices, intelligent systems are revolutionizing by utilizing machine learning. Machine learning as part of intelligent systems is already one of the most critical components in everyday tools ranging from search engines and credit card fraud detection to stock market analysis. You can train machines to perform some things, so that they can automatically detect, diagnose, and solve a variety of problems. The intelligent systems have made rapid progress in developing the state of the art in machine learning based on smart and deep perception. Using machine learning, the intelligent systems make widely applications in automated speech recognition, natural language processing, medical diagnosis, bioinformatics, and robot locomotion. This book aims at introducing how to treat a substantial amount of data, to teach machines and to improve decision making models. And this book specializes in the developments of advanced intelligent systems through machine learning. It consists of 11 contributions that features illumination change detection, generator of electronic educational publications, intelligent call triage system, recognition of rocks at uranium deposits, graphics processing units, mathematical model of hit phenomena, selection and mutation in genetic algorithm, hands and arms motion estimation, application of wavelet network, Kanizsa triangle illusion, and support vector machine regression. Also, it describes how to apply the machine learning for the intelligent systems. This edition is published in original, peer reviewed contributions covering from initial design to final prototypes and verifications.
Soft Computing
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Author : Fred Aminzadeh
language : en
Publisher: Prentice Hall
Release Date : 1994
Soft Computing written by Fred Aminzadeh and has been published by Prentice Hall this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with Application software categories.
This volume presents a collection of articles on state-of-the-art soft computing and AI applications that cover broad domains and many disciplines. The authors explain the evolution of the mathematics behind the intelligent systems; consider fuzzy logic and neural network applications; and explore several AI applications.
Soft Computing And Intelligent Systems
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Author : Madan M. Gupta
language : en
Publisher: Elsevier
Release Date : 1999-10-28
Soft Computing And Intelligent Systems written by Madan M. Gupta and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999-10-28 with Computers categories.
The field of soft computing is emerging from the cutting edge research over the last ten years devoted to fuzzy engineering and genetic algorithms. The subject is being called soft computing and computational intelligence. With acceptance of the research fundamentals in these important areas, the field is expanding into direct applications through engineering and systems science. This book cover the fundamentals of this emerging filed, as well as direct applications and case studies. There is a need for practicing engineers, computer scientists, and system scientists to directly apply "fuzzy" engineering into a wide array of devices and systems.
Handbook Of Machine Learning For Computational Optimization
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Author : Vishal Jain
language : en
Publisher: CRC Press
Release Date : 2021-11-02
Handbook Of Machine Learning For Computational Optimization written by Vishal Jain and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-02 with Technology & Engineering categories.
Technology is moving at an exponential pace in this era of computational intelligence. Machine learning has emerged as one of the most promising tools used to challenge and think beyond current limitations. This handbook will provide readers with a leading edge to improving their products and processes through optimal and smarter machine learning techniques. This handbook focuses on new machine learning developments that can lead to newly developed applications. It uses a predictive and futuristic approach, which makes machine learning a promising tool for processes and sustainable solutions. It also promotes newer algorithms that are more efficient and reliable for new dimensions in discovering other applications, and then goes on to discuss the potential in making better use of machines in order to ensure optimal prediction, execution, and decision-making. Individuals looking for machine learning-based knowledge will find interest in this handbook. The readership ranges from undergraduate students of engineering and allied courses to researchers, professionals, and application designers.