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随机生成和预测Rahuri每周降雨的地区

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水资源管理的主要问题之一是未来的降雨序列的先进的知识或降雨预报。与降雨对水资源的影响已成定局,更准确的预测降雨将使更有效的水资源。根据agro-based地区经济可能极大地受益于降雨量的预测的准确性。这项研究中,因此,特别专注于降雨预报和代以来预测可以为优化管理提供更好的信息资源在相当一段时间。有几个降雨预报技术,包括自回归(AR)和滑动平均(MA)模型不同的订单,ARMA, ARIMA、托马斯Feiring等。这些也称为随机或时间序列模型。自回归综合移动平均(ARIMA)模型更有用的预测和发现了一代的水文事件。因此,在本研究ARIMA模型有不同的订单提前生成和预测降雨。本研究试图开发ARIMA模型预测和代周降雨量。数据收集从印度气象部门国家数据中心,浦那。降雨数据系列的31年(1982 - 2012)Rahuri地区Ahmednagar区用于开发ARIMA模型。 The series of 30 years i.e. from 1982 to 2011 was used for the development of the models and series of 2012 was used for testing the validity of the models. ARIMA models of different orders were selected based on observing autocorrelation functions (ACF) and partial autocorrelation functions (PACF) of the historical rainfall series. The parameters of selected model were obtained with the help of maximum likelihood method. The diagnostic checking of the selected models was then performed with the help of three test (standard error of parameters, ACF and PACF of residuals and Akaike Information Criteria) to know the adequacy of the selected models. The ARIMA models that passed the adequacy test were selected for forecasting. The weekly rainfall values 2012 year were forecasted with the help of these selected models and compared with the actual weekly rainfall values of the year 2012 by root mean square error (RMSE). The ARIMA (1,1,1) (1,0,1) 52 gave the lowest value of RMSE and hence is considered as the best model for generation and forecasting of weekly rainfall values.

p·g . Popale *和s.d Gorantiwar

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