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008			211101s2022 si | s |||| 0|eng d
020			_a9789811647130
024	7		_a10.1007/978-981-16-4713-0 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA76.9 .S63 _b2022 EB
245	0	0	_aSoft Computing in Interdisciplinary Sciences _cedited by S. Chakraverty
250			_a1st edition 2022
264		1	_aSingapore _bSpringer International Publishing _c2022
300			_a1 recurso en línea (XIII, 257 páginas) _b113 ilustraciones, 70 ilustraciones a color
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aStudies in Computational Intelligence _x1860-9503 _v988
505	0		_aChapter 1. Recent Trends in Interval Regression: Applications in Predicting Dengue Outbreaks -- Chapter 2. Fuzzy-Affine Approach in Dynamic Analysis of Uncertain Structural Systems -- Chapter 3. Fuzzy Application: Develop a Weather Index -- Chapter 4. Type-2 Fuzzy Linear Eigenvalue Problems with Application in Dynamic Structures -- Chapter 5. Fuzzy dynamical system in alcohol related health risk behaviors and beliefs -- Chapter 6. Curriculum Learning Based Artificial Neural Network Model for Solving Differential Equations -- Chapter 7. Analysis of EEG signal for drowsy detection: A machine learning approach -- Chapter 8. Uncertain Structural Parameter Identification by Intelligent Neural Training -- Chapter 9. Soft-Computing Tools embedded on Internet-of-Things can enhance Cyber Security -- Chapter 10. Security issues on IoT communication and evolving solutions -- Chapter 11. Causality and Its Applications -- Chapter 12. Hybrid Evolutionary Computing based Association Rule Mining -- Chapter 13. Towards Sarcasm Detection n Reviews - A dual parametric approach with Emojis and Ratings.
520			_aThis 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.
988			_aSpringer_Robotics_2022
650		7	_2embne _9166276 _aSoft Computing
776	0	8	_iPrinted edition: _z9789811647123
776	0	8	_iPrinted edition: _z9789811647147
776	0	8	_iPrinted edition: _z9789811647154
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-16-4713-0 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b03/2023 _dz _eu _zSI