基于反向传播神经网络模型的平武县蜂蜜产值预测

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中图分类号 S898 文献标识码A 文章编号 1007-7731（2025）24-0132-04

DO1号 10.16377/j.cnki.issn1007-7731.2025.24.027

Prediction of honey output value in Pingwu County based on BP neural network model

REN Xianghui LIU Runqiang XING Qiao DUAN YishiSUN Hengfei ZHAO YijiaQIN Mengyan ZHANG ChaoyangYUE WenlongKAN Yunchao （Key Laboratory of Major Crop Pests Prevention and Control in Xinxiang City，School of Resource and Environment Science，Henan Institute of Science and Technology，Xinxiang 453oo3， China）

AbstractBasedonhoneyoutputvalue data from 2O19 to 2023 provided bythe Pingwu County statistics departmentof Sichuan Province，this study established a backpropagation neural network model onthe DPS platform to predicthoney output value，using beeindustry input，honey yield，and sales volumeas independent variablesand honey output valueas the dependentvariable.The results showed that a back-propagation neural network model was developed using the independent and dependent variable data from 2O19 to 2O22 as training samples.The weight values of the neurons for the three independent variables：bee industry input，honeyyield，and salesvolume were-1.11112， -13.976 60，and15.45297，respectively.This model accurately predictedthe trendof honey output value in the following year，with a goodness-of-fit R2 of O.72 between the theoretical and actual values of the dependent variable. The analytical conclusions provide references fordecision-making in the development strategy of the apiculture industry in the region.

Keywords back propagation neural network; DPS platform; honey ouput value; goodness of fit

DPS软件作为全国植保员培训要求掌握的统计学软件，其计算模块包含基本统计学计算、生态学研究以及与各种植物保护相关的专业数据处理模块1]。（剩余4330字）