中国农业科技导报2025，Vol.27Issue(10)：95-104,10.DOI:10.13304/j.nykjdb.2024.0318
基于RSM-GA的稻谷含水率预测模型设计与试验
Design and Experiment of Rice Moisture Content Prediction Model Based on RSM-GA
摘要
Abstract
In order to solve the problems of inaccurate prediction of rice moisture content,large hysteresis and low coefficient of determination during the drying process,the response surface methodology(RSM)was used to analyze the main factors affecting the rice moisture content during drying.Genetic algorithm(GA)was used to optimize the traditional BP(back propagation)neural network model,and a prediction model was established based on RSM-GA,which could accurately predict the moisture content of grain during drying.The results showed that the hot air temperature,grain layer temperature and ambient relative humidity had significant effects on the change of moisture content during drying process of rice.The hot air temperature,grain layer temperature and ambient relative humidity were used as the input layers of the prediction model,the rice moisture content was the output layer.The optimal number of intermediate hidden layers of the prediction model was determined to be 10 through empirical formulas,and the neuron structure of the prediction model established was 3-10-1.During model training,the optimal performance was at the 15 th time,the minimum root mean square error was 0.621 84×10-3,and the optimal Matlab simulation test setting parameters were obtained.When the iterating was to 200 generations,the fitness value was stabilized at 0.019 5.After optimized by genetic algorithm,the coefficient of determination of the prediction model was 0.980,which was 5%higher than the traditional model;the root mean square error was 0.009,which was 17%lower than the traditional model.In summary,the performance of optimized neural network model was improved,which provided a reference for subsequent control strategy research.关键词
稻谷/响应面法/含水率预测/遗传算法/BP神经网络Key words
rice/response surface method/moisture content prediction/genetic algorithm/BP neural network分类
农业科技引用本文复制引用
潘衡,万霖,车刚,王思佳,郑宇,张强..基于RSM-GA的稻谷含水率预测模型设计与试验[J].中国农业科技导报,2025,27(10):95-104,10.基金项目
国家重点研发计划项目(2021YFD2100901) （2021YFD2100901）
黑龙江省应用技术研究与开发计划重大项目(GA15B402). （GA15B402）
