基于KNN-TCN模型的蒸发皿蒸发量预测研究
Prediction of Pan Evaporation Based on KNN-TCN Model
谢育珽 1郑翔天 2史俊才 3刘萍 1申文明 4程文飞 5李新华 6杨静 1邢云飞1
作者信息
- 1. 太原理工大学 大数据学院,山西 太原 030024
- 2. 东北师范大学 经济与管理学院,吉林 长春 130117
- 3. 中国移动通信集团山西有限公司 阳泉分公司,山西 阳泉 045000
- 4. 生态环境部卫星环境应用中心,北京 100094
- 5. 太原理工大学 软件学院,山西 太原 030024
- 6. 吕梁市生态环境局,山西 吕梁 033000
- 折叠
摘要
蒸发量的精确预测对合理开发利用水资源、旱涝变化趋势研究和农作物灌溉用水量的估算具有十分重要的意义.选取我国北方地区 14 个地面国际交换站观测的 7 项气象数据,以时间卷积网络(TCN)模型为基础模型,运用K-近邻(KNN)算法对蒸发皿蒸发量的空间因素进行筛选,构建KNN-TCN蒸发皿蒸发量预测模型,并利用平均绝对误差、均方根误差和判定系数 3 项指标对目标站点的蒸发量预测精度进行评价.结果表明:1)KNN-TCN模型预测结果明显优于LSTM模型;2)相比基础TCN模型,KNN-TCN模型预测结果的判定系数提升了 2.52%,平均绝对误差、均方根误差分别降低了 23.97%、13.06%.
Abstract
Accurate prediction of evaporation is of great significance for the rational development and utilization of water resources,the study of drought and flood trends,and the estimation of crop irrigation water consumption.In this paper,7 meteorological data observed by 14 ground international exchange stations in northern China were selected.Based on the time convolution network(TCN)model,the K-nearest neighbor(KNN)algorithm was used to screen the spatial factors of pan evaporation.The KNN-TCN pan evaporation prediction model was built and the average absolute error,root mean square error and coefficient of determination were used to evaluate the evaporation prediction ac-curacy of the target site.The results show that a)the prediction results of KNN-TCN model are significantly better than that of LSTM model.b)Compared with the basic TCN model,the determination coefficient of KNN-TCN model is increased by 2.52%,and the mean absolute error and root mean square error are reduced by 23.97%and 13.06%,respectively.
关键词
蒸发皿蒸发量/时间卷积网络/K-近邻算法/空间因素Key words
evaporation capacity of evaporating dish/time convolution network/K-nearest neighbor algorithm/spatial factors引用本文复制引用
基金项目
山西省重点研发计划(202202020101007)
山西省自然科学基金青年基金(201901D211002)
出版年
2024
国家科技期刊平台
NSTL
万方数据