基于SOM神经网络的大庆市畜牧生产聚类分析  

Cluster Analysis of Animal Husbandry Production in Daqing Based on SOM Neural Network

作　　者：韦春波[1] 李树春 魏巍[1] 李洋洋[1] 贾永全[1] Wei Chunbo;Li Shuchun;Wei Wei;Li Yangyang;Jia Yongquan(College of Animal Science and Veterinary Medicine,Heilongjiang Bayi Agricultural University,Daqing 163319;Agricultural Bureau of Daqing City Ranghulu District)

机构地区：[1]黑龙江八一农垦大学动物科技学院,大庆163319 [2]大庆市让胡路区农业局

出　　处：《黑龙江八一农垦大学学报》2018年第2期95-99,共5页journal of heilongjiang bayi agricultural university

基　　金：大庆市哲学社会科学规划研究项目(DSGB2017098);大庆市指导性科技计划项目(zd-2016-090)

摘　　要：根据大庆市畜牧业发展的实际,构建了大庆市主要畜禽生产水平的指标体系,设计并建立自组织神经网络模型(SOM),对大庆市各地区的畜牧生产水平进行了聚类分析。结果表明,大庆市各地区的畜牧生产的区划分类结果符合实际,大庆市各地区的畜牧业发展水平不仅与地域资源密切相关,而且与其经济发展水平也紧密联系;同时也充分证明了自组织神经网络(SOM)模型是一种畜牧生产水平聚类分析的新方法。According to the actual development of animal husbandry in Daqing,the index system of the main livestock and poultry production in Daqing was constructed,and a self-organizing neural network model(SOM)was designed and established to cluster the livestock production in all regions of Daqing.The results showed that the classification results of livestock production in all regions of Daqing were in line with the actual situation.The level of animal husbandry in Daqing was closely related to not only the regional resources,but also the level of economic development.At the same time,Self-organizing neural network model(SOM)was a new method of cluster analysis of livestock production level.

关 键 词：大庆市 畜牧生产 SOM 聚类分析 

分 类 号：TP274[自动化与计算机技术—检测技术与自动化装置]