为了科学准确地预测膜下滴灌棉花蒸散量,基于鲸鱼优化算法(whale optimization algorithm,WOA)和极端梯度提升树(XGBoost),提出了 WOA-XGBoost棉花蒸散量预测模型.采用最大互信息系数(maximal information coefficient,MIC)筛选影响棉花蒸散量的关键因素,依据相关系数排序构建输入组合,代入WOA-XGBoost模型进行模拟.并与XGBoost,SVM,WOA-SVM和PSO-XGBoost预测结果进行对比验证.结果表明:太阳辐射、最低气温、最高气温、相对湿度、风速和土壤温度与棉花蒸散量相关性较大,其MIC值分别为0.722,0.546,0.496,0.475,0.379和0.219,基于上述6个因素构建的WOA-XGBoost模型综合性能最优,R2,MAE,RMSE和MAPE分别为0.922,0.038 mm/h,0.064 mm/h和0.221,预测精度均优于相同输入参数下的其他4种模型.因此,推荐使用WOA-XGBoost模型模拟相关因素与膜下滴灌棉花蒸散量之间的非线性关系.研究可为精确计算膜下滴灌棉花蒸散量提供科学依据,为灌溉决策优化提供参考.
Evapotranspiration prediction model of cotton under film drip irrigation based on WOA-XGBoost
To accurately predict cotton evapotranspiration under mulched drip irrigation,a WOA-XG-Boost cotton evapotranspiration prediction model based on the whale optimization algorithm(WOA)and the extreme gradient boosting tree(XGBoost)was proposed.The maximal mutual information coef-ficient(MIC)was utilized to identify the key factors impacting cotton evapotranspiration,and the input combinations were formulated based on the order of correlation coefficients and inputted into the WOA-XGBoost model for simulation.The prediction results were compared and verified with those obtained from XGBoost,SVM,WOA-SVM,and PSO-XGBoost modes.The results show that solar radiation,minimum and maximum air temperatures,relative humidity,wind speed,and soil temperature are highly correlated with cotton evapotranspiration,exhibiting MIC values of 0.722,0.546,0.496,0.475,0.379,and 0.219,respectively.The WOA-XGBoost model constructed on the basis of the above six factors has the best overall performance with R2,MAE,RMSE,and MAPE of 0.922,0.038 mm/h,0.064 mm/h and 0.221,respectively.The predictive accuracy surpass the other four models utilizing the same input parameters.Therefore,it is recommended to use the WOA-XGBoost model to simulate the non-linear relationship between the relevant factors and the evapotranspiration of cotton under film drip irrigation.This study offers a scientific foundation for accurately calculating cotton evapotranspiration under mulched drip irrigation and serves as a reference for optimizing irrigation deci-sions.
evapotranspirationcottonextreme gradient boosting tree modelwhale optimization algorithmprediction model
万方数据
维普
