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001 394702
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008 220708s2022 si | s |||| 0|eng d
020 _a9789811925191
024 7 _a10.1007/978-981-19-2519-1
_2doi
040 _aES-MaUEC
_bspa
_cES-MaUEC
245 1 0 _aComputational Intelligence for Water and Environmental Sciences
_cedited by Omid Bozorg-Haddad, Babak Zolghadr-Asli
250 _a1st edition 2022
264 1 _aSingapore
_bSpringer International Publishing
_c2022
300 _a1 recurso en línea (XXI, 540 páginas)
_b157 ilustraciones, 80 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
_v1043
505 0 _aOptimization Algorithms -- Data mining -- Machine Learning -- Artificial Intelligence -- Deep Learning -- Expert Systems -- Probabilistic Models -- Bayesian models -- Fuzzy logic and Fuzzy Theory.
520 _aThis book provides a comprehensive yet fresh perspective for the cutting-edge CI-oriented approaches in water resources planning and management. The book takes a deep dive into topics like meta-heuristic evolutionary optimization algorithms (e.g., GA, PSA, etc.), data mining techniques (e.g., SVM, ANN, etc.), probabilistic and Bayesian-oriented frameworks, fuzzy logic, AI, deep learning, and expert systems. These approaches provide a practical approach to understand and resolve complicated and intertwined real-world problems that often imposed serious challenges to traditional deterministic precise frameworks. The topic caters to postgraduate students and senior researchers who are interested in computational intelligence approach to issues stemming from water and environmental sciences.
700 1 _aBozorg-Haddad, Omid
_eeditor literario
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aZolghadr-Asli, Babak
_eeditor literario
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
776 0 8 _iPrinted edition:
_z9789811925184
776 0 8 _iPrinted edition:
_z9789811925207
776 0 8 _iPrinted edition:
_z9789811925214
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-19-2519-1
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942 _2lcc
_cLE
988 _aSpringer_Robotics_2022
999 _c394702
_d394702