干旱地区农业研究2017，Vol.35Issue(3)：114-119,6.DOI:10.7606/j.issn.1000-7601.2017.03.18
ET0预测的卡尔曼滤波修正ANFIS模型研究
A study on the modified ANFIS model by the Calman filter for ETo prediction
摘要
Abstract
Real time and accurate prediction for water demand by crop is the key technology to realize intelligent water-saving irrigation.The reasonable selection of forecasting model and the improvement of accuracy is the key to the decision making system on water demand.This article introduced the meteorological data on environmental information in Xi'an of Shaanxi province to the forecast model of self adaptive neural fuzzy inference (ANFIS) reference crop transpiration (ET0).The calman filter was used to filter the noise of the ET0 value obtained by the ANFIS model to improve the forecasting accuracy of the model,thus improving the forecasting accuracy of model and verifying the accuracy of the model through simulation and experiment.The simulation results showed that the equal coefficient(EC) reflecting the fit ting degree between the real value and the result of forecasting model was 0.93 and 0.98 after being adjusted.The results from experiment showed that the ANFIS forecast model's mean absolute error was 28.94％,and the average relative error was 26.37％.After modification,the mean absolute error was 7.24％,and the average relative error was 6.59％.Simulation and experimental results indicated that the prediction model of ANFIS was modified by using caiman filter,which could improve the accuracy of prediction.The revised ANFIS model by the calman had better reflection of the change trend of ET0.关键词
作物参考蒸腾量/彭曼公式/ANFIS预测模型/卡尔曼滤波/预测精度Key words
reference crop evapotranspiration/Penman-Monteith formula/ANFIS model/Caiman filter/prediction accuracy分类
农业科技引用本文复制引用
李志磊,周建平,魏正英,张育斌,许燕..ET0预测的卡尔曼滤波修正ANFIS模型研究[J].干旱地区农业研究,2017,35(3):114-119,6.基金项目
新疆维吾尔自治区高技术研究发展项目“干旱区智能控制微灌技术与设备”(201413102) （201413102）
