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020			_a9783030920265
024	7		_a10.1007/978-3-030-92026-5 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA76.9.S63 _b2022 EB
245	0	0	_aSoft Computing for Data Analytics, Classification Model, and Control _cedited by Deepak Gupta, Aditya Khamparia, Ashish Khanna, Oscar Castillo
250			_aFirst edition 2022
264		1	_aCham _bSpringer International Publishing _c2022
300			_a1 recurso en línea (VIII, 165 páginas) _b83 ilustraciones, 61 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_aarchivo de texto _bPDF
490	0		_aStudies in Fuzziness and Soft Computing _x1860-0808 _v413
505	0		_aChapter 1: An Optimization of Fuzzy Rough Set Nearest Neighbor Classification Model using Krill Herd Algorithm for Sentiment Text Analytics -- Chapter 2: Fuzzy Wavelet Neural Network with Social Spider Optimization Algorithm for Pattern Recognition in Medical Domain -- Chapter 3: Fuzzy with Gravitational Search Algorithm Tuned Radial Basis Function Network for Medical Disease Diagnosis and Classification Model -- Chapter 4: Optimal Neutrosophic Rules based Feature Extraction for Data Classification using Deep Learning Model -- Chapter 5: Self-Evolving Interval Type-2 Fuzzy Neural Network Design for The Synchronization of Chaotic Systems -- Chapter 6: Categorizing Relations via Semi-Supervised Learning using a Hybrid Tolerance Rough Sets and Genetic Algorithm Approach -- Chapter 7: Data-driven Fuzzy C-Means Equivalent Turbine-governor for Power System Frequency Response -- Chapter 8: Multicriteria group decision making using a novel similarity measure for triangular fuzzy numbers based on their newly defined expected values and variances -- Chapter 9: Bangla Printed Character Generation from Handwritten Character Using GAN.
520			_aThis 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.
988			_aSpringer_Robotics_2022
650		7	_2embne _9166276 _aSoft Computing
650		7	_2embne _9421371 _aInteligencia artificial en medicina
650		7	_2embne _9152595 _aSistemas difusos
700	1		_aGupta, Deepak _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aKhamparia, Aditya _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aKhanna, Ashish _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aCastillo, Oscar _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
776	0	8	_iPrinted edition: _z9783030920258
776	0	8	_iPrinted edition: _z9783030920272
776	0	8	_iPrinted edition: _z9783030920289
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-92026-5 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE _n0
998			_b04/2022 _dz _esc _zSI