Rainfall Forecasting Based on Surface Data of Chennai Region Using Artificial Neural Networks

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引用次数: 0

Abstract

In this study, we developed user friendly rainfall forecasting system based on Back propagation Neural Network using MATLAB 7.10 to forecast Hourly rainfall in Chennai region. The dataset of 31488 samples has been collected from Nungambakkam Meteorological Station, Chennai for the period of 2005 to 2015. The data was organized into day-wise hourly recordings as well as day-wise, maximum, minimum, average data of Relative Humidity (RH), Temperature, Pressure and Wind Speed along with Rainfall data. The collected dataset has been used both for training and for testing the data. The developed system gives more accuracy of 94.8197% when the training data set is 55% and the testing data set is 45% with least Mean Squared Error (MSE) value 0.012437.
基于钦奈地区地表数据的人工神经网络降水预报
在本研究中,我们利用MATLAB 7.10开发了基于反向传播神经网络的用户友好型降雨预报系统,用于预测金奈地区的逐时降雨。本文收集了金奈Nungambakkam气象站2005 - 2015年31488个样品的数据集。这些数据被组织成逐日的每小时记录,以及逐日的相对湿度(RH)、温度、压力、风速和降雨量的最大、最小、平均数据。收集的数据集已用于训练和测试数据。当训练数据集为55%,测试数据集为45%时,系统的准确率达到94.8197%,最小均方误差(MSE)为0.012437。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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