An accurate rainfall forecasting is a challenging problem for agriculture dependent countries like India for analyzing the crop productivity, use of water resources and pre-planning of water resources. This book provides issues involved in prediction of daily, monthly, and yearly rainfall data using neural network. We incorporate various models such as ARIMA, Feed Forward Neural Network (FFNN), Radial Basis Function Neural Network (RBFNN), and Time Delay Neural Network (TDNN) techniques for rainfall prediction. All the models implemented using MATLAB software. The purpose of the book is to uses Genetic Algorithm (GA) for optimizing biases and weights of neural network. The results of ARIMA model are compared with the results obtained using three neural network models.
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 88 pp. Englisch. Nº de ref. del artículo: 9786206843993
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Darji MohiniMs. Mohini Darji received her B.E and M.Tech degrees in 2013 and 2015 respectively from Gujarat Technological University (GTU) and Dharmsinh Desai University (DDU). Presently she is working as a Assistant Professor in Com. Nº de ref. del artículo: 1263320491
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -An accurate rainfall forecasting is a challenging problem for agriculture dependent countries like India for analyzing the crop productivity, use of water resources and pre-planning of water resources. This book provides issues involved in prediction of daily, monthly, and yearly rainfall data using neural network. We incorporate various models such as ARIMA, Feed Forward Neural Network (FFNN), Radial Basis Function Neural Network (RBFNN), and Time Delay Neural Network (TDNN) techniques for rainfall prediction. All the models implemented using MATLAB software. The purpose of the book is to uses Genetic Algorithm (GA) for optimizing biases and weights of neural network. The results of ARIMA model are compared with the results obtained using three neural network models.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 88 pp. Englisch. Nº de ref. del artículo: 9786206843993
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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - An accurate rainfall forecasting is a challenging problem for agriculture dependent countries like India for analyzing the crop productivity, use of water resources and pre-planning of water resources. This book provides issues involved in prediction of daily, monthly, and yearly rainfall data using neural network. We incorporate various models such as ARIMA, Feed Forward Neural Network (FFNN), Radial Basis Function Neural Network (RBFNN), and Time Delay Neural Network (TDNN) techniques for rainfall prediction. All the models implemented using MATLAB software. The purpose of the book is to uses Genetic Algorithm (GA) for optimizing biases and weights of neural network. The results of ARIMA model are compared with the results obtained using three neural network models. Nº de ref. del artículo: 9786206843993
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Taschenbuch. Condición: Neu. Rainfall Forecasting Using Neural Network | Mohini Darji (u. a.) | Taschenbuch | Englisch | 2023 | LAP LAMBERT Academic Publishing | EAN 9786206843993 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Nº de ref. del artículo: 128050303
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