摘要
基于BP人工神经网络(BP-ANN)原理,针对农用地分等的问题,设计了BP神经网络农用地分等模型和精度检测方法.结果表明:BP-NN农用地分等模型通过少量典型样本的训练和学习后,可简便、快捷地计算出大规模待定样本的分等综合指数;其泛化功效和精度检测也符合要求.
Based on the theory of BP artificial neural network (BP-ANN), the model for grade of farming land and accuracy measurement were designed. The results from the application to the grade of farming land showed that the grade composition indexes of a large amount of samples could be simply and quickly calculated with the BP-ANN classification model after training and studying a small amount of typical samples, and its popularization function and accuracy also met the expectations.
出处
《福建农林大学学报（自然科学版）》
CSCD
北大核心
2004年第2期241-244,共4页
Journal of Fujian Agriculture and Forestry University:Natural Science Edition
基金
福建省教育厅资助项目(JA002211).
