LEADER 02323nam 2200373 450 001 9910729788803321 005 20230730114016.0 024 7 $a10.3390/books978-3-0365-7578-0 035 $a(CKB)4960000000468957 035 $a(NjHacI)994960000000468957 035 $a(EXLCZ)994960000000468957 100 $a20230730d2023 uy 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aSoft Computing and Machine Learning in Dam Engineering /$fedited by M. Amin Hariri-Ardebili [and four others] 210 1$aBasel, Switzerland :$cMDPI - Multidisciplinary Digital Publishing Institute,$d2023. 215 $a1 online resource (260 pages) 311 $a3-0365-7578-2 330 $a"Soft Computing and Machine Learning in Dam Engineering" is a comprehensive, edited Special Issue that explores the latest advances in the application of soft computing and machine learning techniques to dam engineering. This reprint covers a range of topics, including dam design, construction, monitoring, and maintenance, and provides readers with a deep understanding of the theoretical foundations and practical applications of these techniques.Featuring contributions from leading experts in the field, the reprint presents a collection of 11 papers that offer insights into state-of-the-art approaches in dam engineering. The chapters cover topics such as fuzzy logic, genetic algorithms, artificial neural networks, and support vector machines, and provide practical examples of how these techniques can be applied to solve real-world dam engineering problems.Whether you are a researcher, engineer, or student in the field of dam engineering, "Soft Computing and Machine Learning in Dam Engineering" provides a valuable resource for staying up-to-date with the latest techniques and approaches in the field. 606 $aDams$xDesign and construction 606 $aArtificial intelligence 615 0$aDams$xDesign and construction. 615 0$aArtificial intelligence. 676 $a627.8 702 $aHariri-Ardebili$b M. Amin 801 0$bNjHacI 801 1$bNjHacl 906 $aBOOK 912 $a9910729788803321 996 $aSoft Computing and Machine Learning in Dam Engineering$93392047 997 $aUNINA