北京林业大学学报2024，Vol.46Issue(8)：94-100,7.DOI:10.12171/j.1000-1522.20230166
基于BP神经网络的落叶松树冠体积及表面积模型构建
Model construction of Larix principis-rupprechtii canopy volume and surface area based on BP neural network
摘要
Abstract
[Objective]The BP neural network model was applied to predict the canopy volume and surface area of Larix principis-rupprechtii,and the optimal form of canopy volume and surface area estimation model of L. principis-rupprechtii was explored in order to provide new ideas for the future prediction model.[Method]Taking L. principis-rupprechtii in Pangquangou Nature Reserve of Shanxi Province,northern China as the research object,the canopy volume and surface area of L. principis-rupprechtii were constructed using BP neural network based on 678 observational data obtained from six (60 m × 60 m) fixed plots.[Result]Through model training,the canopy volume and surface area estimation model of L. principis-rupprechtii was obtained based on BP neural network. Based on BP neural network,the number of input layer nodes∶number of hidden layer nodes∶number of output layer nodes was 6∶9∶1. Canopy volume data R2=0.948,MAE=5.40 m3,RMSE=18.40;surface area data R2=0.957,MAE=3.33 m2,RMSE=14.41. The performance of L. principis-rupprechtii canopy volume and surface area model based on BP neural network was positively correlated with the number of input factors. The optimal model had 6 input factors,i.e. crown width,tree height,DBH,max. crown height,projection length of the first live branch in the direction perpendicular to trunk,and crown base height.[Conclusion]The input variables include information related to trunk size and crown configuration characteristics. The model can realize the prediction for the crown volume and surface area of Larix principis-rupprechtii trees effectively.关键词
模型构建/树冠体积与表面积/BP神经网络/机器学习/预测模型/华北落叶松Key words
model buildings/canopy volume and surface area/BP neural network/machine learning/prediction model/Larix principis-rupprechtii分类
林学引用本文复制引用
周来,程小芳,张梦弢..基于BP神经网络的落叶松树冠体积及表面积模型构建[J].北京林业大学学报,2024,46(8):94-100,7.基金项目
山西省高等学校科技创新项目(2021L138),北京林业大学中央高校基本科研业务费专项(BFUKF202304),山西农业大学博士科研启动项目(2021BQ15),国家自然科学基金青年科学基金项目(31901308). （2021L138）
