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

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Joseph D. Novak,Alberto J. Cañas impact analysis of development scenarios are of significant importance in case of the changing environment. Considering the complexity of natural phenomena as well as our limited knowledge of mathematical modeling, this might be a challenging problem. Recently, development of data-driven models has

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Joseph D. Novak,Alberto J. Cañasmathematical 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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Research in Mathematics Educationed methods are used to model and forecast time series data such as autoregressive (AR) and autoregressive moving average (ARMA) models, autoregressive integrated moving average (ARIMA) model, and autoregressive moving average with exogenous (ARMAX) data. Time series modeling involves techniques that

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https://doi.org/10.1007/978-3-030-80008-6 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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Silvia Zorzetto,Francesco Ferraroector machine (SVM) is a concept for a set of related supervised learning methods that analyze data and recognize patterns, used for classification and regression analysis. The formulation of SVM uses the structural risk minimization principle, which has been shown to be superior to the traditional