利用人工神经网络、全球定位系统和气象资料预报雨量

A. Sachan
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引用次数: 5

摘要

降雨及其变率的预报对于许多现实生活中的应用,如水文循环,是很重要的。此外,对次大陆国家的及时降雨预测在经济上很重要,因为它们是农业经济。此外,降雨对许多自然灾害如滑坡、洪水等起着巨大的作用。然而,准确预测降雨的时间和大小仍然很复杂,因为它取决于许多参数,如水蒸气、压力、温度、风速等。在本文中,我们提出了一个智能系统来预测班加罗尔地区的降雨。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Forecasting of rainfall using ANN, GPS and mteorological data
Forecasting of rainfall and its variability is important for many real life applications such as hydrological cycle. Further, timely rainfall prediction for subcontinent countries is economically important because they have agro-based economy. Moreover, rainfall play huge role for many natural disasters such as landslide, flush flood etc. However, accurate prediction of rainfall in terms of timing and magnitude is still remains complex because it depends upon many parameters like water vapor, pressure, temperature, wind velocity etc. In this paper we have proposed an intelligent system to predict the rainfall for Bangalore region.
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