CAJ | 학술논문

在林地资产评估中，将 BP 神经网络与批量评估方法结合，通过对影响林地资产评估价值因子的数据处理，建立林地批量评估 BP 模型，运用贝叶斯方法估计正则化参数，提高 BP 网络模型泛化能力。结果表明，基于贝叶斯正则化的 BP 神经网络模型能够实现批量预估林地资产价值，其评估结果精度可靠，泛化能力很好，可为集体林区林地资产评估提供一种新的思路与方法。
재임지자산평고중，장 BP 신경망락여비량평고방법결합，통과대영향임지자산평고개치인자적수거처리，건립임지비량평고 BP 모형，운용패협사방법고계정칙화삼수，제고 BP 망락모형범화능력。결과표명，기우패협사정칙화적 BP 신경망락모형능구실현비량예고임지자산개치，기평고결과정도가고，범화능력흔호，가위집체림구임지자산평고제공일충신적사로여방법。
The BP model for mass evaluation of forestland was established by integrating the BP neural network with the mass appraisal method,and by dealing with the data of factors influencing upon the appraisal value of forestland assets.The generalization ability of BP network model was enhanced by estimating the regularization parameter with Bayesian method.The results showed that the BP neural network model based on Bayesian regulari-zation was able to evaluate the value of forestland assets in batch,with an accurate result and good generalization a-bility.This model could provide the collective forestland assets evaluation with a new thinking and approach.