基于GA-BP神经网络的新疆南疆核桃树生长模型研究
Research on the growth model of walnut trees in southern Xinjiang based on GA-BP neural network
陈杰1
作者信息
- 1. 塔里木大学,新疆 阿拉尔 843300
- 折叠
摘要
文章提出了一种利用遗传算法优化BP神经网络的核桃树生长模型来预测核桃树的树高、胸径的方法,通过优化BP神经网络的权值和阈值建立GA-BP 模型,与多元线性回归模型的预测结果进行比较.结果表明:采用遗传算法优化后的模型具有更高的预测精度,对核桃树生长预测具有指导意义.
Abstract
A walnut tree growth model using genetic algorithm to optimize BP neural network was proposed to predict the tree height and diameter at breast height of walnut trees,and the GA-BP model was established by optimizing the weights and thresholds of BP neural network,and the prediction results were compared with those of multiple linear regression model.The results show that the model optimized with genetic algorithm has higher prediction accuracy and is of guiding significance for walnut tree growth prediction.
关键词
遗传算法/DB神经网络/GA-BP模型/核桃树生长模型Key words
genetic algorithm/DB neural network/GA-BP model/walnut tree growth model引用本文复制引用
基金项目
塔里木大学校长基金(TDZKYB202202)
出版年
2024
NETL
NSTL
万方数据