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Comparative study of ANFIS and ARIMA model for weather forecasting in Dhaka

机译:达卡天气预报的ANFIS和ARIMA模型的比较研究

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Significant amount of research have been carried out and various models have been developed by the researchers for weather forecasting. In this paper we present a comparative study of ARIMA (Auto-Regressive Integrated Moving Average) and ANFIS (Adaptive Network Based Fuzzy Inference System) models for forecasting the weather conditions in Dhaka, Bangladesh. Ten years weather data (from year 2000 to 2009), i.e., Maximum Temperature, Minimum Temperature, Humidity and Air Pressure are used in this research. We have compared the models with difference performance metric, for example, with Mean Absolute Error (MAE), Root Mean Square Error (RMSE), R-square error and the Sum of Square Error (SSE). Experimental results demonstrate that ARIMA has better performance compared to ANFIS. In this study, SPSS is used to carry out experiments on ARIMA model and Fuzzy Logic Toolbox in Matlab is used for ANFIS model.
机译:研究人员进行了大量研究,研究人员开发了各种天气预报模型。在本文中,我们对ARIMA(自回归综合移动平均)和ANFIS(基于自适应网络的模糊推理系统)模型进行了比较研究,以预测孟加拉国达卡的天气情况。这项研究使用了十年的天气数据(从2000年到2009年),即最高温度,最低温度,湿度和气压。我们将模型与差异性能指标进行了比较,例如平均绝对误差(MAE),均方根误差(RMSE),R平方误差和平方误差总和(SSE)。实验结果表明,ARIMA比ANFIS具有更好的性能。在本研究中,SPSS用于ARIMA模型进行实验,而Matlab中的Fuzzy Logic Toolbox用于ANFIS模型。

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