How Fuzzy Concepts Contribute To Machine Learning
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How Fuzzy Concepts Contribute To Machine Learning
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Author : Mahdi Eftekhari
language : en
Publisher: Springer Nature
Release Date : 2022-02-15
How Fuzzy Concepts Contribute To Machine Learning written by Mahdi Eftekhari and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-15 with Technology & Engineering categories.
This book introduces some contemporary approaches on the application of fuzzy and hesitant fuzzy sets in machine learning tasks such as classification, clustering and dimension reduction. Many situations arise in machine learning algorithms in which applying methods for uncertainty modeling and multi-criteria decision making can lead to a better understanding of algorithms behavior as well as achieving good performances. Specifically, the present book is a collection of novel viewpoints on how fuzzy and hesitant fuzzy concepts can be applied to data uncertainty modeling as well as being used to solve multi-criteria decision making challenges raised in machine learning problems. Using the multi-criteria decision making framework, the book shows how different algorithms, rather than human experts, are employed to determine membership degrees. The book is expected to bring closer the communities of pure mathematicians of fuzzy sets and data scientists.
2020 International Conference On Data Mining Workshops Icdmw
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Author : IEEE Staff
language : en
Publisher:
Release Date : 2020-11-17
2020 International Conference On Data Mining Workshops Icdmw written by IEEE Staff and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-17 with categories.
The conference covers all aspects of data mining, including algorithms, software and systems, and applications
Deep Learning And Neural Networks Concepts Methodologies Tools And Applications
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Author : Management Association, Information Resources
language : en
Publisher: IGI Global
Release Date : 2019-10-11
Deep Learning And Neural Networks Concepts Methodologies Tools And Applications written by Management Association, Information Resources and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-11 with Computers categories.
Due to the growing use of web applications and communication devices, the use of data has increased throughout various industries. It is necessary to develop new techniques for managing data in order to ensure adequate usage. Deep learning, a subset of artificial intelligence and machine learning, has been recognized in various real-world applications such as computer vision, image processing, and pattern recognition. The deep learning approach has opened new opportunities that can make such real-life applications and tasks easier and more efficient. Deep Learning and Neural Networks: Concepts, Methodologies, Tools, and Applications is a vital reference source that trends in data analytics and potential technologies that will facilitate insight in various domains of science, industry, business, and consumer applications. It also explores the latest concepts, algorithms, and techniques of deep learning and data mining and analysis. Highlighting a range of topics such as natural language processing, predictive analytics, and deep neural networks, this multi-volume book is ideally designed for computer engineers, software developers, IT professionals, academicians, researchers, and upper-level students seeking current research on the latest trends in the field of deep learning.
Fuzzy Systems Modeling In Environmental And Health Risk Assessment
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Author : Boris Faybishenko
language : en
Publisher: John Wiley & Sons
Release Date : 2023-03-21
Fuzzy Systems Modeling In Environmental And Health Risk Assessment written by Boris Faybishenko and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-21 with Science categories.
Fuzzy Systems Modeling in Environmental and Health Risk Assessment Demonstrates the successful application of fuzzy systems modeling to real-world environmental and health problems In Fuzzy Systems Modeling in Environmental and Health Risk Assessment, a team of distinguished researchers delivers an up-to-date collection of the most successful and innovative attempts to apply fuzzy logic to problems involving environmental risk assessment, healthcare decision-making, the management of water distribution networks, and the optimization of water treatment and waste management systems. By explaining both the theoretical and practical aspects of using fuzzy systems modeling methods to solve complex problems, analyze risks and optimize system performance, this handy guide maintains a strongly application-oriented perspective throughout, offering readers a practical treatment of a cutting-edge subject. Readers will also find: Comprehensive explorations of the practical applications of fuzzy systems modeling in environmental science Practical advice on environmental quality assessments and human health risk analyses In-depth case studies involving air and water pollution, solid waste, indoor swimming pool and landfill risk assessments, wastewater treatment, and more Perfect for environmental engineers and scientists, Fuzzy Systems Modeling in Environmental and Health Risk Assessment will also benefit policy makers, computer scientists, mathematicians, and researchers and practitioners interested in applying soft computing theories to environmental problems.
Nature Inspired Computation And Machine Learning
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Author : Alexander Gelbukh
language : en
Publisher: Springer
Release Date : 2014-11-05
Nature Inspired Computation And Machine Learning written by Alexander Gelbukh and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-05 with Computers categories.
The two-volume set LNAI 8856 and LNAI 8857 constitutes the proceedings of the 13th Mexican International Conference on Artificial Intelligence, MICAI 2014, held in Tuxtla, Mexico, in November 2014. The total of 87 papers plus 1 invited talk presented in these proceedings were carefully reviewed and selected from 348 submissions. The first volume deals with advances in human-inspired computing and its applications. It contains 44 papers structured into seven sections: natural language processing, natural language processing applications, opinion mining, sentiment analysis, and social network applications, computer vision, image processing, logic, reasoning, and multi-agent systems, and intelligent tutoring systems. The second volume deals with advances in nature-inspired computation and machine learning and contains also 44 papers structured into eight sections: genetic and evolutionary algorithms, neural networks, machine learning, machine learning applications to audio and text, data mining, fuzzy logic, robotics, planning, and scheduling, and biomedical applications.
Icdsmla 2019
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Author : Amit Kumar
language : en
Publisher: Springer Nature
Release Date : 2020-05-19
Icdsmla 2019 written by Amit Kumar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-19 with Technology & Engineering categories.
This book gathers selected high-impact articles from the 1st International Conference on Data Science, Machine Learning & Applications 2019. It highlights the latest developments in the areas of Artificial Intelligence, Machine Learning, Soft Computing, Human–Computer Interaction and various data science & machine learning applications. It brings together scientists and researchers from different universities and industries around the world to showcase a broad range of perspectives, practices and technical expertise.
Empirical Approach To Machine Learning
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Author : Plamen P. Angelov
language : en
Publisher: Springer
Release Date : 2018-10-17
Empirical Approach To Machine Learning written by Plamen P. Angelov and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-17 with Computers categories.
This book provides a ‘one-stop source’ for all readers who are interested in a new, empirical approach to machine learning that, unlike traditional methods, successfully addresses the demands of today’s data-driven world. After an introduction to the fundamentals, the book discusses in depth anomaly detection, data partitioning and clustering, as well as classification and predictors. It describes classifiers of zero and first order, and the new, highly efficient and transparent deep rule-based classifiers, particularly highlighting their applications to image processing. Local optimality and stability conditions for the methods presented are formally derived and stated, while the software is also provided as supplemental, open-source material. The book will greatly benefit postgraduate students, researchers and practitioners dealing with advanced data processing, applied mathematicians, software developers of agent-oriented systems, and developers of embedded and real-time systems. Itcan also be used as a textbook for postgraduate coursework; for this purpose, a standalone set of lecture notes and corresponding lab session notes are available on the same website as the code. Dimitar Filev, Henry Ford Technical Fellow, Ford Motor Company, USA, and Member of the National Academy of Engineering, USA: “The book Empirical Approach to Machine Learning opens new horizons to automated and efficient data processing.” Paul J. Werbos, Inventor of the back-propagation method, USA: “I owe great thanks to Professor Plamen Angelov for making this important material available to the community just as I see great practical needs for it, in the new area of making real sense of high-speed data from the brain.” Chin-Teng Lin, Distinguished Professor at University of Technology Sydney, Australia: “This new book will set up a milestone for the modern intelligent systems.” Edward Tunstel, President of IEEE Systems, Man, Cybernetics Society, USA: “Empirical Approach to Machine Learning provides an insightful and visionary boost of progress in the evolution of computational learning capabilities yielding interpretable and transparent implementations.”
Cognitive Analytics Concepts Methodologies Tools And Applications
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Author : Management Association, Information Resources
language : en
Publisher: IGI Global
Release Date : 2020-03-06
Cognitive Analytics Concepts Methodologies Tools And Applications written by Management Association, Information Resources and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-06 with Science categories.
Due to the growing use of web applications and communication devices, the use of data has increased throughout various industries, including business and healthcare. It is necessary to develop specific software programs that can analyze and interpret large amounts of data quickly in order to ensure adequate usage and predictive results. Cognitive Analytics: Concepts, Methodologies, Tools, and Applications provides emerging perspectives on the theoretical and practical aspects of data analysis tools and techniques. It also examines the incorporation of pattern management as well as decision-making and prediction processes through the use of data management and analysis. Highlighting a range of topics such as natural language processing, big data, and pattern recognition, this multi-volume book is ideally designed for information technology professionals, software developers, data analysts, graduate-level students, researchers, computer engineers, software engineers, IT specialists, and academicians.
Machine Learning And Artificial Intelligence Concepts Algorithms And Models
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Author : Reza Rawassizadeh
language : en
Publisher: Reza Rawassizadeh
Release Date : 2025-03-15
Machine Learning And Artificial Intelligence Concepts Algorithms And Models written by Reza Rawassizadeh and has been published by Reza Rawassizadeh this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-15 with Computers categories.
Mastering AI, machine learning, and data science often means piecing together concepts scattered across countless resources—from statistics and visualizations to foundational models and large language models. This book, the result of eight years of effort, brings it all together in one accessible, engaging package. It clarifies artificial intelligence and data science, blending core mathematical principles with a clear, reader-friendly approach. Unlike traditional textbooks that lean heavily on equations and mathematical formalization, the author starts with minimal prerequisites, layering deeper math as the reader progresses. Each concept, algorithm, or model is unpacked through clear, hands-on examples that build the reader's skills step by step. It strikes a balance between theoretical foundations and practical application, serving as both an academic reference and a practical guide. Furthermore, the book uses humor, casual language, and comics to make the challenging concepts and topics relatable and fun. Any resemblance between the jokes and real life is pure coincidence, and no offense is intended.
Interpretability In Deep Learning
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Author : Ayush Somani
language : en
Publisher: Springer Nature
Release Date : 2023-04-30
Interpretability In Deep Learning written by Ayush Somani and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-30 with Computers categories.
This book is a comprehensive curation, exposition and illustrative discussion of recent research tools for interpretability of deep learning models, with a focus on neural network architectures. In addition, it includes several case studies from application-oriented articles in the fields of computer vision, optics and machine learning related topic. The book can be used as a monograph on interpretability in deep learning covering the most recent topics as well as a textbook for graduate students. Scientists with research, development and application responsibilities benefit from its systematic exposition.