Maximum Temperature Prediction Based on GPS and Meteorological Data by Using Neural Network

Shenzheng Zuo, Renjie Cai, Yan Wang, Enrui Hu, Lingzhi Liu, Yibo Guo
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Abstract

Temperature prediction is a task involving agriculture, military, industry and other aspects, and it is related to daily life and production tasks. Therefore, accurate temperature prediction is an important research topic at present. In this paper, a neural network-based maximum temperature prediction method is proposed. Combined with the Precipitable Water Vapor (PWV) data calculated from GPS satellite data, it achieves high precision, high time granularity prediction under the condition of low computing power requirements.
基于GPS和气象资料的神经网络最高气温预报
温度预报是一项涉及农业、军事、工业等多方面的任务,关系到日常生活和生产任务。因此,准确的温度预测是当前重要的研究课题。本文提出了一种基于神经网络的最高温度预测方法。结合GPS卫星数据计算的可降水量(PWV)数据,在对计算能力要求较低的条件下,实现了高精度、高时间粒度的预测。
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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