基于BP神经网络的气温预报

ZhengCun Jiang, Wenping Jiang
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引用次数: 0

摘要

气温的变化与人们的生活密切相关,第二天气温的剧烈变化会影响人们的正常生活,因此准确预测第二天的气温是非常重要的。信息融合技术是为了完成所需的决策和评估任务,对多源信息进行自动分析和综合处理的过程。BP神经网络是一种信息融合算法,可以对各种传感器采集的数据进行预测。因此,对堪培拉传感器采集到的最高气温、最低气温、降雨量、最大风速等数据进行处理,构建BP神经网络预测次日的最高气温和最低气温。实验结果表明,该方法能较好地预测次日的最高和最低气温。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Forecast of air temperature based on BP neural network
The change of temperature is closely related to people's life, and the drastic change of the next day's temperature will affect people's normal life, so it is very important to accurately predict the next day's temperature. Information fusion technology is a process of automatic analysis and comprehensive processing of multi-source information in order to complete the required decision-making and evaluation tasks. BP neural network is one of the information fusion algorithms, which can predict the data collected by various sensors. Therefore, the data collected by Canberra sensor, such as maximum temperature, minimum temperature, rainfall and maximum wind speed, are processed, and the BP neural network is constructed to predict the maximum and minimum temperature of the next day. The experimental results show that this method can well predict the maximum and minimum temperature of the next day.
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