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Soft Computing for Data Analytics, Classification Model, and Control: 413 (Studies in Fuzziness and Soft Computing) - Tapa dura
Sinopsis
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.
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De la contraportada
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 ofhybrid algorithms for applications in data analytics, classification model, and engineering control.
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Soft Computing for Data Analytics, Classification Model, and Control.
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Cham, Springer International Publishing : Imprint: Springer., 2022
ISBN 10: 3030920259
ISBN 13: 9783030920258
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1st ed. 2022. VIII, 165 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Studies in Fuzziness and Soft Computing, 413. Sprache: Englisch. Nº de ref. del artículo: 2653LB
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Soft Computing for Data Analytics, Clas (eng)
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Soft Computing for Data Analytics Classification Model and Control (eng)
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Soft Computing for Data Analytics, Classification Model, and Control (Hardcover)
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Springer Nature Switzerland AG, Cham, 2022
ISBN 10: 3030920259
ISBN 13: 9783030920258
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Hardcover. Condición: new. Hardcover. 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 ofhybrid algorithms for applications in data analytics, classification model, and engineering control. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9783030920258
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Soft Computing for Data Analytics, Classification Model, and Control (Studies in Fuzziness and Soft Computing, 413)
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Soft Computing for Data Analytics, Classification Model, and Control (Studies in Fuzziness and Soft Computing, 413)
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Soft Computing for Data Analytics, Classification Model, and Control
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ISBN 10: 3030920259
ISBN 13: 9783030920258
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Soft Computing for Data Analytics, Classification Model, and Control (Studies in Fuzziness and Soft Computing, 413)
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Soft Computing for Data Analytics, Classification Model, and Control
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Springer, Berlin|Springer International Publishing|Springer, 2022
ISBN 10: 3030920259
ISBN 13: 9783030920258
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Soft Computing for Data Analytics, Classification Model, and Control
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Springer International Publishing Jan 2022, 2022
ISBN 10: 3030920259
ISBN 13: 9783030920258
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents a setof 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 ofhybrid algorithms for applications in data analytics, classification model, and engineering control. 176 pp. Englisch. Nº de ref. del artículo: 9783030920258
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