%0 Journal Article
%T New Measure for Forecasting Sales and Stores of Goods<br>一种预测商品销量及库存的新方法*
%A YOU Xiao-fang
%A QIN Ze
%A CHEN Feng
%A WANG Zhan
%A ZHANG Shi-chao
%A <br>尤晓芳
%A 覃泽
%A 陈峰
%A 汪展
%A 张师超
%J 计算机应用研究
%D 2007
%I 
%X Abstract:Sliding window on vertical time axis is first used for selecting historical data similar to the predicted goods. Historical data in the sliding window is processed using both Pearson Correlation and average value generation function so as to improve the flexibility of the algorithm and the prediction accuracy. The remarkable advantages of the approach include filtering exceptional data, and generating the trends of sales of goods. Some experiments demonstrate that this algorithm is efficiency at both the time complexity and promising accuracy.
%K Sliding Window
%K Pearson Correlation(PC)
%K Exception Filter
%K Trend Forecast
%K Vertical Analysis<br>滑动窗口
%K Pearson
%K Correlation
%K 过滤异常
%K 预测变化趋势
%K 纵向分析
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=343459AF1736CA692581D87DF91A7641&yid=A732AF04DDA03BB3&vid=B91E8C6D6FE990DB&iid=CA4FD0336C81A37A&sid=1D0FA33DA02ABACD&eid=E84BBBDDD74F497C&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=7