| 书目名称 | Data-Driven Modeling: Using MATLAB® in Water Resources and Environmental Engineering |
| 编辑 | Shahab Araghinejad |
| 视频video | |
| 概述 | Designed as a textbook.Over fourty source codes applied to be developed with MATLAB are provided.Additional illustrative examples treating common problems in water resources and environmental engineer |
| 丛书名称 | Water Science and Technology Library |
| 图书封面 |  |
| 描述 | .“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 |
| 出版日期 | Textbook 2014 |
| 关键词 | Data-Driven Models; Empirical Models; Environmental Models; Hydrological Models; Water Resources Models |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-94-007-7506-0 |
| isbn_softcover | 978-94-024-0589-7 |
| isbn_ebook | 978-94-007-7506-0Series ISSN 0921-092X Series E-ISSN 1872-4663 |
| issn_series | 0921-092X |
| copyright | Springer Science+Business Media Dordrecht 2014 |
发表于 2025-3-21 16:09:42
