Fuzzy Computing in Data Science

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Publisher : John Wiley & Sons
ISBN 13 : 1394156863
Total Pages : 373 pages
Book Rating : 4.63/5 ( download)

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Book Synopsis Fuzzy Computing in Data Science by : Sachi Nandan Mohanty

Download or read book Fuzzy Computing in Data Science written by Sachi Nandan Mohanty and published by John Wiley & Sons. This book was released on 2022-11-03 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: FUZZY COMPUTING IN DATA SCIENCE This book comprehensively explains how to use various fuzzy-based models to solve real-time industrial challenges. The book provides information about fundamental aspects of the field and explores the myriad applications of fuzzy logic techniques and methods. It presents basic conceptual considerations and case studies of applications of fuzzy computation. It covers the fundamental concepts and techniques for system modeling, information processing, intelligent system design, decision analysis, statistical analysis, pattern recognition, automated learning, system control, and identification. The book also discusses the combination of fuzzy computation techniques with other computational intelligence approaches such as neural and evolutionary computation. Audience Researchers and students in computer science, artificial intelligence, machine learning, big data analytics, and information and communication technology.

Soft Computing for Data Analytics, Classification Model, and Control

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Publisher : Springer Nature
ISBN 13 : 3030920267
Total Pages : 165 pages
Book Rating : 4.65/5 ( download)

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Book Synopsis Soft Computing for Data Analytics, Classification Model, and Control by : Deepak Gupta

Download or read book Soft Computing for Data Analytics, Classification Model, and Control written by Deepak Gupta and published by Springer Nature. This book was released on 2022-01-30 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a set of soft computing approaches and their application in data analytics, classification model, and control. The basics of fuzzy logic implementation for advanced hybrid fuzzy driven optimization methods has been covered in the book. The various soft computing techniques, including Fuzzy Logic, Rough Sets, Neutrosophic Sets, Type-2 Fuzzy logic, Neural Networks, Generative Adversarial Networks, and Evolutionary Computation have been discussed and they are used on variety of applications including data analytics, classification model, and control. The book is divided into two thematic parts. The first thematic section covers the various soft computing approaches for text classification and data analysis, while the second section focuses on the fuzzy driven optimization methods for the control systems. The chapters has been written and edited by active researchers, which cover hypotheses and practical considerations; provide insights into the design of hybrid algorithms for applications in data analytics, classification model, and engineering control.

Fuzzy Logic in Artificial Intelligence

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Publisher : Springer
ISBN 13 : 9783662166703
Total Pages : 203 pages
Book Rating : 4.04/5 ( download)

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Book Synopsis Fuzzy Logic in Artificial Intelligence by : Erich P. Klement

Download or read book Fuzzy Logic in Artificial Intelligence written by Erich P. Klement and published by Springer. This book was released on 2014-03-12 with total page 203 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains the proceedings of the Eighth Austrian Artificial Intelligence Conference, held in Linz, Austria, in June 1993. The focus of the conference was on "Fuzzy Logic in Artificial Intelligence". The volume contains abstracts of two invited talks and full versions of 17 carefully selected papers. The invited talks were: "The role of fuzzylogic and soft computing in the conception and design of intelligent systems" by Lotfi A. Zadeh, and "A contextual approach for AI systems development" by Irina V. Ezhkova. The contributed papers are grouped into sections on theoretical issues, machine learning, expert systems, robotics and control, applications to medicine, and applications to car driving. Additionally, the volume contains descriptions of the four workshops that took place during the conference.

Linguistic Fuzzy Logic Methods in Social Sciences

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Publisher : Springer Science & Business Media
ISBN 13 : 3642133428
Total Pages : 194 pages
Book Rating : 4.28/5 ( download)

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Book Synopsis Linguistic Fuzzy Logic Methods in Social Sciences by : Badredine Arfi

Download or read book Linguistic Fuzzy Logic Methods in Social Sciences written by Badredine Arfi and published by Springer Science & Business Media. This book was released on 2010-06-17 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book, titled “Linguistic Fuzzy-Logic Methods in Social Sciences,” is a first in its kind. Linguistic fuzzy logic theory deals with sets or categories whose boundaries are blurry or, in other words, “fuzzy,” and which are expressed in a formalism that uses “words” to compute, not numbers, termed in engineering as “soft computing.” This book presents an accessible introduction to this linguistic fuzzy logic methodology, focusing on its applicability to social sciences. Specifically, this is the first book to propose an approach based on linguistic fuzzy-logic and the method of computing with words to the analysis of decision making processes, strategic interactions, causality, and data analysis in social sciences. The project consists of systematic, theoretical and practical discussions and developments of these new methods as well as their applications to various substantive issues of interest to international relations scholars, political scientists, and social scientists in general.

Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making

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Publisher : Springer
ISBN 13 : 3030237567
Total Pages : 1392 pages
Book Rating : 4.61/5 ( download)

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Book Synopsis Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making by : Cengiz Kahraman

Download or read book Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making written by Cengiz Kahraman and published by Springer. This book was released on 2019-07-05 with total page 1392 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes the proceedings of the Intelligent and Fuzzy Techniques INFUS 2019 Conference, held in Istanbul, Turkey, on July 23–25, 2019. Big data analytics refers to the strategy of analyzing large volumes of data, or big data, gathered from a wide variety of sources, including social networks, videos, digital images, sensors, and sales transaction records. Big data analytics allows data scientists and various other users to evaluate large volumes of transaction data and other data sources that traditional business systems would be unable to tackle. Data-driven and knowledge-driven approaches and techniques have been widely used in intelligent decision-making, and they are increasingly attracting attention due to their importance and effectiveness in addressing uncertainty and incompleteness. INFUS 2019 focused on intelligent and fuzzy systems with applications in big data analytics and decision-making, providing an international forum that brought together those actively involved in areas of interest to data science and knowledge engineering. These proceeding feature about 150 peer-reviewed papers from countries such as China, Iran, Turkey, Malaysia, India, USA, Spain, France, Poland, Mexico, Bulgaria, Algeria, Pakistan, Australia, Lebanon, and Czech Republic.

Data Science and Knowledge Engineering for Sensing Decision Support

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Publisher : World Scientific
ISBN 13 : 9813273240
Total Pages : 1624 pages
Book Rating : 4.45/5 ( download)

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Book Synopsis Data Science and Knowledge Engineering for Sensing Decision Support by : Jun Liu

Download or read book Data Science and Knowledge Engineering for Sensing Decision Support written by Jun Liu and published by World Scientific. This book was released on 2018-07-26 with total page 1624 pages. Available in PDF, EPUB and Kindle. Book excerpt: FLINS, originally an acronym for Fuzzy Logic and Intelligent Technologies in Nuclear Science, is now extended to include Computational Intelligence for applied research. The contributions of the FLINS conference cover state-of-the-art research, development, and technology for computational intelligence systems, with special focuses on data science and knowledge engineering for sensing decision support, both from the foundations and the applications points-of-view.

Dynamic Fuzzy Machine Learning

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Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3110520656
Total Pages : 337 pages
Book Rating : 4.51/5 ( download)

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Book Synopsis Dynamic Fuzzy Machine Learning by : Fanzhang Li

Download or read book Dynamic Fuzzy Machine Learning written by Fanzhang Li and published by Walter de Gruyter GmbH & Co KG. This book was released on 2017-12-04 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning is widely used for data analysis. Dynamic fuzzy data are one of the most difficult types of data to analyse in the field of big data, cloud computing, the Internet of Things, and quantum information. At present, the processing of this kind of data is not very mature. The authors carried out more than 20 years of research, and show in this book their most important results. The seven chapters of the book are devoted to key topics such as dynamic fuzzy machine learning models, dynamic fuzzy self-learning subspace algorithms, fuzzy decision tree learning, dynamic concepts based on dynamic fuzzy sets, semi-supervised multi-task learning based on dynamic fuzzy data, dynamic fuzzy hierarchy learning, examination of multi-agent learning model based on dynamic fuzzy logic. This book can be used as a reference book for senior college students and graduate students as well as college teachers and scientific and technical personnel involved in computer science, artificial intelligence, machine learning, automation, data analysis, mathematics, management, cognitive science, and finance. It can be also used as the basis for teaching the principles of dynamic fuzzy learning.

Intelligent Techniques for Data Science

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Publisher : Springer
ISBN 13 : 3319292064
Total Pages : 272 pages
Book Rating : 4.69/5 ( download)

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Book Synopsis Intelligent Techniques for Data Science by : Rajendra Akerkar

Download or read book Intelligent Techniques for Data Science written by Rajendra Akerkar and published by Springer. This book was released on 2016-10-11 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides readers with the tools, techniques and cases required to excel with modern artificial intelligence methods. These embrace the family of neural networks, fuzzy systems and evolutionary computing in addition to other fields within machine learning, and will help in identifying, visualizing, classifying and analyzing data to support business decisions./p> The authors, discuss advantages and drawbacks of different approaches, and present a sound foundation for the reader to design and implement data analytic solutions for real‐world applications in an intelligent manner. Intelligent Techniques for Data Science also provides real-world cases of extracting value from data in various domains such as retail, health, aviation, telecommunication and tourism.

Fuzzy Intelligent Systems

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Publisher : John Wiley & Sons
ISBN 13 : 1119760453
Total Pages : 482 pages
Book Rating : 4.50/5 ( download)

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Book Synopsis Fuzzy Intelligent Systems by : E. Chandrasekaran

Download or read book Fuzzy Intelligent Systems written by E. Chandrasekaran and published by John Wiley & Sons. This book was released on 2021-09-08 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: FUZZY INTELLIGENT SYSTEMS A comprehensive guide to Expert Systems and Fuzzy Logic that is the backbone of artificial intelligence. The objective in writing the book is to foster advancements in the field and help disseminate results concerning recent applications and case studies in the areas of fuzzy logic, intelligent systems, and web-based applications among working professionals and those in education and research covering a broad cross section of technical disciplines. Fuzzy Intelligent Systems: Methodologies, Techniques, and Applications comprises state-of-the-art chapters detailing how expert systems are built and how the fuzzy logic resembling human reasoning, powers them. Engineers, both current and future, need systematic training in the analytic theory and rigorous design of fuzzy control systems to keep up with and advance the rapidly evolving field of applied control technologies. As a consequence, expert systems with fuzzy logic capabilities make for a more versatile and innovative handling of problems. This book showcases the combination of fuzzy logic and neural networks known as a neuro-fuzzy system, which results in a hybrid intelligent system by combining a human-like reasoning style of neural networks. Audience Researchers and students in computer science, Internet of Things, artificial intelligence, machine learning, big data analytics and information and communication technology-related fields. Students will gain a thorough understanding of fuzzy control systems theory by mastering its contents.

Advances in Computing and Data Sciences

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Publisher : Springer
ISBN 13 : 9811318131
Total Pages : 578 pages
Book Rating : 4.39/5 ( download)

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Book Synopsis Advances in Computing and Data Sciences by : Mayank Singh

Download or read book Advances in Computing and Data Sciences written by Mayank Singh and published by Springer. This book was released on 2018-10-25 with total page 578 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set (CCIS 905 and CCIS 906) constitutes the refereed proceedings of the Second International Conference on Advances in Computing and Data Sciences, ICACDS 2018, held in Dehradun, India, in April 2018. The 110 full papers were carefully reviewed and selected from 598 submissions. The papers are centered around topics like advanced computing, data sciences, distributed systems organizing principles, development frameworks and environments, software verification and validation, computational complexity and cryptography, machine learning theory, database theory, probabilistic representations.