使用径向基函数神经网络进行印度瓦朗加尔的天气预报

IF 2.1 Q3 ENVIRONMENTAL SCIENCES
V. Veeramsetty, P. Kiran, Munjampally Sushma, S. Salkuti
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引用次数: 0

摘要

天气预报在世界任何地区都是一项重要任务,对受气候变化影响的各个部门进行适当规划。在瓦兰加尔,农业和电力等大多数部门主要受到气候条件的影响。在这项研究中,根据温度和湿度对瓦朗加尔地区的天气(WX)进行了预测。本研究采用径向基函数神经网络对湿度和温度进行预测。收集了2021年1月至2021年12月期间的湿度和温度数据。基于仿真结果,可以观察到径向基函数神经网络模型在预测温度和湿度时比其他机器学习模型表现更好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Weather Forecasting Using Radial Basis Function Neural Network in Warangal, India
Weather forecasting is an essential task in any region of the world for proper planning of various sectors that are affected by climate change. In Warangal, most sectors, such as agriculture and electricity, are mainly influenced by climate conditions. In this study, weather (WX) in the Warangal region was forecast in terms of temperature and humidity. A radial basis function neural network was used in this study to forecast humidity and temperature. Humidity and temperature data were collected for the period of January 2021 to December 2021. Based on the simulation results, it is observed that the radial basis function neural network model performs better than other machine learning models when forecasting temperature and humidity.
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来源期刊
CiteScore
4.30
自引率
0.00%
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审稿时长
11 weeks
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