气象Issue(7)：881-885,5.DOI:10.7519/j.issn.1000-0526.2014.07.012
遗忘因子自适应最小二乘算法及其在气温预报中的应用
Forgetting-Factor Adaptive Least Square Algorithm and Its Application in Temperature Forecasting
摘要
Abstract
A mass of data is the foundation of adaptive forecasting model.However,the role of new incom-ing data will be gradually reduced and the performance of the model will become poor with the data increas-ing.In order to overcome the influence of “data saturation”on the weather forecast,the method of adap-tive linear least square modeling algorithm considering forgetting factors is developed and applied in max-min temperature forecast.The results show that this adaptive linear least square modeling algorithm con-sidering forgetting factors is superior to the traditional adaptive linear modeling algorithm,it can reduce the effect of “data saturation”by using the forgetting factor,and it is possible to improve the model’s forecast accuracy by choosing the appropriate forgetting factors.关键词
遗忘因子/自适应建模/最小二乘法/气温预报Key words
forgetting factor/adaptive modeling/least square algorithm/temperature forecast分类
天文与地球科学引用本文复制引用
翟宇梅,赵瑞星,高建春,王力维,韩海东..遗忘因子自适应最小二乘算法及其在气温预报中的应用[J].气象,2014,(7):881-885,5.基金项目
省部级2009年重点科研项目“概率天气预报业务系统”资助 （）
