LEADER 05624nam 22008415 450 001 9910298385303321 005 20200705183213.0 010 $a94-007-7506-7 024 7 $a10.1007/978-94-007-7506-0 035 $a(CKB)3710000000078682 035 $a(DE-He213)978-94-007-7506-0 035 $a(SSID)ssj0001066873 035 $a(PQKBManifestationID)11694864 035 $a(PQKBTitleCode)TC0001066873 035 $a(PQKBWorkID)11080765 035 $a(PQKB)11675938 035 $a(MiAaPQ)EBC6312471 035 $a(MiAaPQ)EBC1591877 035 $a(Au-PeEL)EBL1591877 035 $a(CaPaEBR)ebr10962618 035 $a(OCoLC)922907372 035 $a(PPN)176129448 035 $a(EXLCZ)993710000000078682 100 $a20131125d2014 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aData-Driven Modeling: Using MATLAB® in Water Resources and Environmental Engineering /$fby Shahab Araghinejad 205 $a1st ed. 2014. 210 1$aDordrecht :$cSpringer Netherlands :$cImprint: Springer,$d2014. 215 $a1 online resource (XIII, 292 p. 142 illus., 79 illus. in color.) 225 1 $aWater Science and Technology Library,$x0921-092X ;$v67 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a94-007-7505-9 320 $aIncludes bibliographical references and index. 327 $aPreface -- 1. Introduction -- 2. Basic Statistics -- 3. Regression Based Models -- 4. Time Series Modeling -- 5. Artificial Neural Networks -- 6. Support Vector Machines.- 7. Fuzzy Models -- 8. Hybrid Models and Multi Model Data Fusion -- Appendix -- Index.   . 330 $a?Data-Driven Modeling: Using MATLAB® in Water Resources and Environmental Engineering? provides a systematic account of major concepts and methodologies for data-driven models and presents a unified framework that makes the subject more accessible to and applicable for researchers and practitioners. It integrates important theories and applications of data-driven models and uses them to deal with a wide range of problems in the field of water resources and environmental engineering such as hydrological forecasting, flood analysis, water quality monitoring, regionalizing climatic data, and general function approximation. The book presents the statistical-based models including basic statistical analysis, nonparametric and logistic regression methods, time series analysis and modeling, and support vector machines. It also deals with the analysis and modeling based on artificial intelligence techniques including static and dynamic neural networks, statistical neural networks, fuzzy inference systems, and fuzzy regression. The book also discusses hybrid models as well as multi-model data fusion to wrap up the covered models and techniques.    The source files of relatively simple and advanced programs demonstrating how to use the models are presented together with practical advice on how to best apply them. The programs, which have been developed using the MATLAB® unified platform, can be found on extras.springer.com. The main audience of this book includes graduate students in water resources engineering, environmental engineering, agricultural engineering, and natural resources engineering. This book may be adapted for use as a senior undergraduate and graduate textbook by focusing on selected topics. Alternatively, it may also be used as a valuable resource book for practicing engineers, consulting engineers, scientists and others involved in water resources and environmental engineering. 410 0$aWater Science and Technology Library,$x0921-092X ;$v67 606 $aHydrogeology 606 $aHydrology 606 $aEnvironmental sciences 606 $aWater$xPollution 606 $aEnvironmental monitoring 606 $aEnvironmental management 606 $aHydrogeology$3https://scigraph.springernature.com/ontologies/product-market-codes/G19005 606 $aHydrology/Water Resources$3https://scigraph.springernature.com/ontologies/product-market-codes/211000 606 $aMath. Appl. in Environmental Science$3https://scigraph.springernature.com/ontologies/product-market-codes/U24005 606 $aWaste Water Technology / Water Pollution Control / Water Management / Aquatic Pollution$3https://scigraph.springernature.com/ontologies/product-market-codes/U35040 606 $aMonitoring/Environmental Analysis$3https://scigraph.springernature.com/ontologies/product-market-codes/U1400X 606 $aEnvironmental Management$3https://scigraph.springernature.com/ontologies/product-market-codes/U17009 615 0$aHydrogeology. 615 0$aHydrology. 615 0$aEnvironmental sciences. 615 0$aWater$xPollution. 615 0$aEnvironmental monitoring. 615 0$aEnvironmental management. 615 14$aHydrogeology. 615 24$aHydrology/Water Resources. 615 24$aMath. Appl. in Environmental Science. 615 24$aWaste Water Technology / Water Pollution Control / Water Management / Aquatic Pollution. 615 24$aMonitoring/Environmental Analysis. 615 24$aEnvironmental Management. 676 $a620.00151 700 $aAraghinejad$b Shahab$4aut$4http://id.loc.gov/vocabulary/relators/aut$01065136 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910298385303321 996 $aData-Driven Modeling: Using MATLAB® in Water Resources and Environmental Engineering$92543303 997 $aUNINA