检索结果-南通市图书馆

Modelling reference evapotranspiration using gene expression programming and artificial neural network at Pantnagar,India

引用

Information Processing in Agriculture 2023年第4期10卷 547-563页

作者： pangam heramb Pramod Kumar Singh K.V.Ramana Rao A.Subeesh Division of Irrigation and Drainage Engineering ICAR-Central Institute of Agricultural EngineeringBhopal 462038India Department of Irrigation and Drainage Engineering G.B.Pant University of Agriculture and TechnologyPantnagar 263145India Division of Agricultural Mechanization ICAR-Central Institute of Agricultural EngineeringBhopal 462038India

Evapotranspiration is an essential component of the hydrological cycle that is of particular interest for water resource *** quantification is helpful in irrigation scheduling,water balance studies,water allocation,*** of reference evapotranspiration(ET0)using both gene expression programming(GEP)and artificial neural network(ANN)techniques was done using the daily meteorological data of the Pantnagar region,India,from 2010 to 2019.A total of 15 combinations of inputs were used in developing the ET0 *** model with the least number of inputs consisted of maximum and minimum air temperatures,whereas the model with the highest number of inputs consisted of maximum air temperature,minimum air temperature,mean relative humidity,number of sunshine hours,wind speed at 2mheight and extra-terrestrial radiation as inputs and with ET0 as the output for all the *** the GEP models were developed for a single functional set and pre-defined genetic operator values,while the best structure in each ANN model was found based on the performance during the testing *** was found that ANN models were superior to GEP models for the estimation *** was evident from the reduction in RMSE values ranging from 2%to 56%during training and testing phases in all the ANN models compared with GEP *** ANN models showed an increase of about 0.96%to 9.72%of R2 value compared to the respective GEP *** comparative study of these models with multiple linear regression(MLR)depicted that the ANN and GEP models were superior to MLR models.

关键词： Artificial Neural Networks Evolutionary algorithms Gene Expression Programming Machine Learning Regression Analysis Reference evapotranspiration models

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：