Weather Forecasting Using Artificial Neural Network

Dires Negash Fente, Dheeraj Kumar Singh
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引用次数: 51

Abstract

Accurate weather forecast plays a vital role in today's world as agricultural and indusrial sectors are principally dependent on weather conditions. It is also used to forecast and warm about natural disasters. Weather forecasting is determination of the right values of weather parameters and furhermore the future weather condition based on these parameters. In this study different weather parameters were collected from national climate data center then using Long-short term memory(LSTM) technique, the neural network is trained for different combinations. In prediction of future weather condition using LSTM the neural network is trained using different combinations of weather parameters, the weather parameters used are temperature, precipitation, wind speed. pressure, dew point visibility and humidity. After training of LSTM model using these parameters the prediction of future weather is done.
利用人工神经网络进行天气预报
准确的天气预报在当今世界起着至关重要的作用,因为农业和工业部门主要依赖天气条件。它还用于自然灾害的预报和预警。天气预报就是确定天气参数的正确值,进而根据这些参数预测未来的天气状况。本研究从国家气候数据中心收集不同的天气参数,利用长短期记忆(LSTM)技术对神经网络进行不同组合的训练。在使用LSTM预测未来天气条件时,神经网络使用不同的天气参数组合进行训练,使用的天气参数是温度,降水,风速。压力、露点能见度和湿度。利用这些参数对LSTM模型进行训练后,对未来天气进行预测。
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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