摘要
利用模糊物元模型对玉米螟的种群动进行预测,在利用信息熵理论确定预报因子的权重的基础上构造了复合模糊物元模型,并根据往年资料构造出用于预测的关联度区间,以预测关联度映射的区间进行判决,这样避免了传统分级方法造成的主观误差,同时提高了预测的精度.
Using Fuzzy matter element model to forecast the population dynamics of the corn borer is analyzed. Information entropy is used to determine the weights of the evaluation indexes then compound Fuzzy matter element model is constructed. The area of relationship degree is constructed for forecast with the former years' data and the later population is judged with the casting area of the forecast relationship degree. This method can avoid the subjective error of traditional classification and improve the veracity of forecast.
出处
《数学的实践与认识》
CSCD
北大核心
2007年第10期78-82,共5页
Mathematics in Practice and Theory
基金
国家自然科学基金项目(40574001)
山东农业大学博士科研基金(23241)
关键词
玉米螟
预测预报
物元模型
熵权
corn borer
forecast
matter element model
entropy weight