| 云冷杉天然林林分年龄预测——以金沟岭林场为例 |
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| 引用本文： | 宁杨翠,郑小贤,刘东兰,孔令红,陈宝升.云冷杉天然林林分年龄预测——以金沟岭林场为例[J].西北林学院学报,2012(1):158-162. |
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| 作者姓名： | 宁杨翠 郑小贤 刘东兰 孔令红 陈宝升 |
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| 作者单位： | 国务院参事室战略研究中心;北京林业大学省部共建森林培育与保护教育部重点实验室;吉林省金沟岭林场 |
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| 基金项目： | 林业分益性行业科研专项的我国典型森林类型健康经营关键技术研究(20100400203) |
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| 摘 要： | 应用BP神经网络模型、PPR神经网络模型以及多元逐步回归模型,依据林分因子预测了金沟岭林场云冷杉天然林林分年龄。对比分析了人工神经网络计算模型算法与多元逐步回归分析模型预测结果的精度以及稳定性。结果表明:3种模型均可用于天然林林分年龄的预测,BP神经网络模型的预测平均相对误差为0.04,模型稳定性差;PPR神经网络模型的预测相对误差为0.06,模型稳定性好;多元逐步回归模型的预测相对误差为0.08,模型稳定性好。
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| 关 键 词： | BP神经网络模型 PPR神经网络模型 多元逐步回归分析模型 林分年龄 |
Forecasting the Spruce-fir Natural Forest Stand Age in Jingouling Forest Farm |
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| NING Yang-cui,ZHENG Xiao-xian,LIU Dong-lan,KONG Ling-hong,CHEN Bao-sheng.Forecasting the Spruce-fir Natural Forest Stand Age in Jingouling Forest Farm[J].Journal of Northwest Forestry University,2012(1):158-162. |
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| Authors: | NING Yang-cui ZHENG Xiao-xian LIU Dong-lan KONG Ling-hong CHEN Bao-sheng |
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| Institution: | 1.Counselor’s Office of the State Council;2.The Key Laboratory for Silviculture and Conservation of Ministry of Education Beijing Forestry University Beijing 100083,China;3.Jingouling Forest farm Wangging,Jilin 132021,China) |
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| Abstract: | The back propagation(BP) artificial neural network(ANN),the projection pursuit regression(PPR)(ANN) and the multiple stepwise regression anatomic(MSRA) models were introduced to predict the nonlinear relation between the natural stand age and the stand factors.The precision and stabilities of the models were testified.The results indicated that 3 kinds of models were applicable for the prediction of natural forest age.The predication average relative error was 0.04 for model of BP ANN,0.06 for PPR ANN,and 0.08 for the MSRA model.The stability of BP ANN model was poor,and the PPR model and MSRA model were stable.It was concluded that the PPR model was better than the other two models,which can be applied to predict the natural forest stand age. |
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| Keywords: | BP artificial neural network model PPR artificial neural network mode multiple stepwise regression anatomic models stands age |
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