Data-driven modeling [electronic resource] : using MATLAB© in water resources and environmental engineering / Shahab Araghinejad.
2014
TD353
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Details
Title
Data-driven modeling [electronic resource] : using MATLAB© in water resources and environmental engineering / Shahab Araghinejad.
Author
Araghinejad, Shahab, author.
ISBN
9789400775060 electronic book
9400775067 electronic book
9789400775053
9400775067 electronic book
9789400775053
Published
Dordrecht : Springer, 2014.
Language
English
Description
1 online resource (xiii, 292 pages) : illustrations (some color).
Item Number
10.1007/978-94-007-7506-0 doi
Call Number
TD353
Dewey Decimal Classification
628.1028553
Summary
"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.
Bibliography, etc. Note
Includes bibliographical references and index.
Access Note
Access limited to authorized users.
Source of Description
Description based on online resource; title from PDF title page (SpringerLink, viewed December 3, 2013).
Series
Water science and technology library ; 67. 0921-092X
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Table of Contents
Basic Statistics
Regression Based Models
Time Series Modeling
Artificial Neural Networks
Support Vector Machines
Fuzzy Models
Hybrid Models and Multi Model Data Fusion.
Regression Based Models
Time Series Modeling
Artificial Neural Networks
Support Vector Machines
Fuzzy Models
Hybrid Models and Multi Model Data Fusion.