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Titlebook: Computational Intelligence Techniques in Earth and Environmental Sciences; Tanvir Islam,Prashant K. Srivastava,Saumitra Mukhe Book 2014 Sp

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Stories, Storytellers, and Storytellingvariation using the resistant smoothing method, 4253H-twice. The SARMA(2, 1)(1, 2). model was found to be the most appropriate model for forecasting. The fitted model is also stable with no structural change and thus applicable for forecasting and policy purposes. Finally, this model was used for fo
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,Gerichtliche L?schungsklage eines Dritten, In this way, noise reduction of data using an appropriate de-noising scheme may lead to a better performance in the application of the data-driven ANN model. Thereupon, in this chapter, the ANN-based hydrological models (i.e., stream-flow and sediment) were developed by focusing on wavelet-based gl
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Vector Autoregression (VAR) Modeling and Forecasting of Temperature, Humidity, and Cloud Coverage C.W.J. Granger. The order of the VAR model was selected using Akaike information criterion, Schwarz information criteria, Hannan–Quinn information criteria, final prediction error, and likelihood ratio test. The ordinary least square method was used to estimate the parameters of the model. The VAR(
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