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Titlebook: Data-Driven Modeling: Using MATLAB? in Water Resources and Environmental Engineering; Shahab Araghinejad Textbook 2014 Springer Science+Bu

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發(fā)表于 2025-3-21 16:09:42 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Data-Driven Modeling: Using MATLAB? in Water Resources and Environmental Engineering
編輯Shahab Araghinejad
視頻videohttp://file.papertrans.cn/264/263303/263303.mp4
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
叢書名稱Water Science and Technology Library
圖書封面Titlebook: Data-Driven Modeling: Using MATLAB? in Water Resources and Environmental Engineering; Shahab Araghinejad Textbook 2014 Springer Science+Bu
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
關鍵詞Data-Driven Models; Empirical Models; Environmental Models; Hydrological Models; Water Resources Models
版次1
doihttps://doi.org/10.1007/978-94-007-7506-0
isbn_softcover978-94-024-0589-7
isbn_ebook978-94-007-7506-0Series ISSN 0921-092X Series E-ISSN 1872-4663
issn_series 0921-092X
copyrightSpringer Science+Business Media Dordrecht 2014
The information of publication is updating

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Basic Statistics,mathematical models, . is described by the probability theory using probability distribution function (.). Regarding the type of a random variable which might be discrete or continuous, it is defined by two types of discrete and continuous .s. Discrete distribution functions of ., ., and . are revie
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Artificial Neural Networks, relationship between neurons in different layers. Neuron is a mathematical unit, and an artificial neural network that consists of neurons is a complex and nonlinear system. Artificial neural networks (ANNs) may have different architectures which result in different types of ANNs. A static ANN know
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Hybrid Models and Multi-model Data Fusion,i-model ensemble estimations are applied to increase accuracy and precision of single models. To get an idea about how different models could be combined in a way to increase each other’s abilities, the chapter begins with a summary on the characteristics of the models presented in the previous chap
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https://doi.org/10.1007/978-3-030-12068-9ce systems, and fuzzy regression are the main subjects which are presented in this chapter. Obviously, the related useful MATLAB commands are presented and discussed to support the methods of applied modeling of the presented subjects.
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