CAJ | 학술논문

文章简要分析了BP神经网络的结构和学习过程，然后以1978—2009年的中国乳业规模发展数据为基础，以奶牛年末存栏数（千头）、奶牛养殖业产值、畜牧业总产值等三个变量作为输入、中国奶牛产量作为输出，采用MATLAB2009a中的BP神经网络工具箱构建了基于BP神经网络的中国乳业发展规模预测模型。研究结果表明：未来十年中国原奶产量将大幅度增长，乳业规模将迅速扩大，原料奶生产无组织管理已不适应乳业经济的迅猛发展，“十二五”期间必须转变原料奶总量的增长方式。研究成果对于奶牛养殖业管理部门、养殖业者科学合理地规划奶牛养殖规模具有重要的参考价值。
문장간요분석료BP신경망락적결구화학습과정，연후이1978—2009년적중국유업규모발전수거위기출，이내우년말존란수（천두）、내우양식업산치、축목업총산치등삼개변량작위수입、중국내우산량작위수출，채용MATLAB2009a중적BP신경망락공구상구건료기우BP신경망락적중국유업발전규모예측모형。연구결과표명：미래십년중국원내산량장대폭도증장，유업규모장신속확대，원료내생산무조직관리이불괄응유업경제적신맹발전，“십이오”기간필수전변원료내총량적증장방식。연구성과대우내우양식업관리부문、양식업자과학합리지규화내우양식규모구유중요적삼고개치。
This article briefly analyzes BP Neural Network＇ s structure and its learning process, and then takes the quality of dairy herds at the end of the year, the value of dairy cow industry and total value of livestock industry as three input variables, dairy cow milk output in China as output, with the data of Chinese Dairy Industry scale from 1978 to 2009 as the base;it creates a model to predict Chinese dairy industry development scale upon BP Neural Network with the using of BP Neural Network tool box form MATLAB2009a. The research result shows that in the following 10 years Chinese raw milk output will increase heavily and dairy industry scale will expand rapidly, which requires more than non -organized raw milk production management. During ＂the 12th 5 -year -plan＂period, the increasing way of raw milk production must be changed. The result is of important reference for cow farming management department and cow farmers to plan and control cow farming scale.