Rainfall Prediction using Subtractive Clustering and Levenberg-Marquardt Algorithms

S. Sunori, Amit Mittal, Dr Sudhanshu Maurya, P. Negi, S. Arora, K. A. Joshi, P. Juneja
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引用次数: 2

Abstract

The subject of present paper is the rainfall prediction with knowledge of two input parameters on which the rainfall is strongly connected i.e temperature and humidity. The rainfall forecasting, in India, is a challenging task due to significantly fluctuating nature of weather here. In the present work, artificial intelligence (AI) techniques are used to train a prediction model for the forecasting of the amount of rainfall. The two considered input parameters, for this model, are temperature and humidity. The prediction models have been designed, using MATLAB, using two different AI approaches, one is the subtractive clustering and another is the Levenberg-Marquardt algorithm. Finally, their prediction performance is considered.
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基于减法聚类和Levenberg-Marquardt算法的降雨预测
本文的主题是降雨预测与两个输入参数的知识,雨量是强连接的,即温度和湿度。在印度,降雨预报是一项具有挑战性的任务,因为这里的天气波动很大。在目前的工作中,使用人工智能(AI)技术来训练预测模型,用于预测降雨量。对于这个模型,考虑的两个输入参数是温度和湿度。利用MATLAB设计了预测模型,采用了两种不同的人工智能方法,一种是减法聚类,另一种是Levenberg-Marquardt算法。最后,考虑了它们的预测性能。
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