基于优化LM模糊神经网络的不均衡林业信息文本分类算法  

Uneven forestry information text classifi cation algorithm based on optimization LM fuzzy neural network

作　　者：陈宇[1] 许莉薇 

机构地区：[1]东北林业大学信息与计算机工程学院,黑龙江哈尔滨150040

出　　处：《中南林业科技大学学报》2015年第4期27-32,59,共7页Journal of Central South University of Forestry & Technology

基　　金：国家948项目(2011-4-04);中央高校基本科研业务费专项资金项目(DL12CB02);黑龙江省教育厅科学技术研究项目(12513016);黑龙江省博士后基金;黑龙江省自然科学基金项目(F201347);哈尔滨市科技创新人才专项资金项目(2013RFQXJ100)

摘　　要：为解决不均衡林业信息文本分类中少数类分类正确率低问题,提出了一种基于优化LM模糊神经网络的不均衡林业信息文本分类算法。在阐述优化LM模糊神经网络算法原理的基础上,提取不均衡林业信息文本特征矩阵训练分类器的各项参数,实现对不均衡林业信息文本的精准与快速分类。实验结果表明该算法对少数类辨识准确率高,优于神经网络分类法以及SVM算法、模糊神经网络算法,为不均衡林业信息文本的分类提供了新思路。In order to deal with the problem of low categorization accuracy of minority class of the uneven forestry information text classification algorithm, the uneven forestry information text classification algorithm was puts forward based on optimization LM fuzzy neural network （OLM-FNN）. On the basis of expounding the principle of optimization LM fuzzy neural network （FNN）, the parameters feature matrix training classifier of uneven forestry information text to of LM fuzzy neural network were extracted, thus realizing accurate and fast classification to uneven forestry information text. The experimental results show that the algorithm had higher classification accuracy of minority class than that of neural network and support vector machine （SVM） and fuzzy neural network. The algorithm provides new ideas for studying on uneven forestry information text classification algorithm.

关 键 词：不均衡文本分类算法 不均衡林业信息文本分类 优化LM模糊神经网络 分类器 

分 类 号：S757.3[农业科学—森林经理学]