基于BP神经网络对苹果呼吸强度的预测  

Prediction of Respiration Intensity of Apple Based on BP Neural Network

作　　者：李宏文[1] 董庆利[1] 杨佳丽[1] 屠康[1] 

机构地区：[1]南京农业大学食品科技学院农业部农畜产品加工与质量控制重点开放实验室,江苏南京210095

出　　处：《江苏农业学报》2007年第4期335-339,共5页Jiangsu Journal of Agricultural Sciences

基　　金：国家自然科学基金项目(30270765);江苏省自然科学基金项目(BK2006707-2);教育部"新世纪优秀人才支持计划"(NCET-05-0491)

摘　　要：应用BP神经网络,通过苹果贮藏期间多维数据与呼吸强度的相关分析确定网络的拓扑结构,建立苹果呼吸强度的人工神经网络模型。仿真结果表明,该神经网络能很好地拟合不同贮藏条件下的呼吸强度,模型预测精度达到90%以上。同时,通过遗传算法优化BP神经网络的初始权值和阈值矩阵,使神经网络的预测精度进一步提高。A network topological structure was determined and an artificial neural network model for predicting respiration rate of Red Fuji apple during storage was established by using BP neural network. The correlation between multi-dimension input data and respiration rate was reported. Compared to the determined respiration rate under different storage conditions, the BP neural network model well predicted the respiration rate with the prediction precision above 90%. Meanwhile, the optimization of the weight and threshold of matrix by the application of genetic algorithms of BP neural network can improve the prediction precision.

关 键 词：BP神经网络 呼吸强度 预测 遗传算法 

分 类 号：S611.109[农业科学—园艺学]