刘溅洪,罗来正,王健坤,李茜,吴欣睿,孙有美.区域历史气压数据预测方法研究[J].装备环境工程,2025,22(2):167-172. LIU Jianhong,LUO Laizheng,WANG Jiankun,LI Qian,WU Xinrui,SUN Youmei.Forecasting Methods of Regional Historical Atmospheric Pressure[J].Equipment Environmental Engineering,2025,22(2):167-172.
区域历史气压数据预测方法研究
Forecasting Methods of Regional Historical Atmospheric Pressure
投稿时间:2024-09-03  修订日期:2024-12-18
DOI:10.7643/issn.1672-9242.2025.02.019
中文关键词:  历史环境因素  样条函数  时间序列模型  时空分布模型  边界条件  预测中图分类号:P426.6 文献标志码:A 文章编号:1672-9242(2025)02-0167-06
英文关键词:historical environmental factors  spline function  time series model  spatiotemporal distribution model  boundary conditions  prediction
基金项目:
作者单位
刘溅洪 西南技术工程研究所,重庆 400039 
罗来正 西南技术工程研究所,重庆 400039 
王健坤 西南技术工程研究所,重庆 400039 
李茜 西南技术工程研究所,重庆 400039 
吴欣睿 西南技术工程研究所,重庆 400039 
孙有美 西南技术工程研究所,重庆 400039 
AuthorInstitution
LIU Jianhong Southwest Institute of Technology and Engineering, Chongqing 400039, China 
LUO Laizheng Southwest Institute of Technology and Engineering, Chongqing 400039, China 
WANG Jiankun Southwest Institute of Technology and Engineering, Chongqing 400039, China 
LI Qian Southwest Institute of Technology and Engineering, Chongqing 400039, China 
WU Xinrui Southwest Institute of Technology and Engineering, Chongqing 400039, China 
SUN Youmei Southwest Institute of Technology and Engineering, Chongqing 400039, China 
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中文摘要:
      目的 研究区域气压、温度、湿度等典型环境因素历史数据的精确预测方法。方法 通过分析气压的时空变化规律,采用样条函数拟合气压在时间维度上的变化规律,利用高斯分布刻画不同站点间空间上的相关性,构建区域历史气压数据时空分布模型。结果 模型对海南岛某站气压数据拟合值与实测值的最大绝对误差不超过0.8 hPa,平均绝对误差不超过0.2 hPa。模型对海南岛某站气压的预测平均绝对误差在6 hPa以下(占比95.3%),对高原地区某站气压的预测平均绝对误差约为29.5 hPa,平均相对误差为4.6%,预测精度较高。结论 采用构建的时空分布模型能够为区域环境因素极值计算提供更多的基础数据,该方法还可以广泛应用于绝对湿度、温度等环境因素边界条件的预测。
英文摘要:
      The work aims to research the accurate prediction method of historical data of regional typical environmental factors, such as pressure, temperature and humidity. Specifically, by analyzing the spatial and temporal variation of atmospheric pressure, spline function was used to fit the temporal variation, and Gaussian distribution was used to depict the spatial correlation between different stations. Then, a spatial and temporal distribution model of regional historical environmental factors was constructed. Results showed that the maximum absolute error and the average absolute error between the fitted and measured atmospheric pressure data of a station in Hainan Island were less than 0.8 hPa and 0.2 hPa respectively.In addition, the average absolute error of the model for a station in Hainan Island was less than 6 hPa (95.3%), which was about 29.5 hPa for a station in the plateau area. Meanwhile, the average relative error was about 4.6%, indicating high prediction accuracy of the model. Therefore, the constructed spatiotemporal distribution model provides more basic data for the calculation of the extremesdata of regional historical environmental factors, and it also provides new ideas for predicting boundary conditions of environmental factors such as absolute humidity and temperature.
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