摘要
利用时序加权平均(time order weight averaging operator,TOWA)算子和时序几何平均(time orderweighted geometric averaging operator,TOWGA)算子对时序立体数据进行降维处理,并给出了确定时间权重的最小方差法。在事先给定的时间度的情况下,尽可能地寻找一组最稳定的时间权重系数来集结样本值,即寻找一组时间权重系数使其波动最小。最后,运用该方法进行了算例分析,并且将算例结果与熵值规划法进行了比较分析,验证了方法的有效性,总结了最小方差法的特点。
Data dimension is decreased by using time order weighted averaging operator（TOWA） and time order weighted geometric averaging operator（TOWGA）,then the minimal variability weighting vector method is introduced,which determines the minimal variability weighting vector under the given level of time orness.An example is also discussed to compare numerical results with entropy-programming method and minimal variability weighting vector method,some conclusions are gained by comparison.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2010年第6期1225-1228,共4页
Systems Engineering and Electronics
关键词
动态综合评价
时间度
时序加权平均算子
最小方差法
dynamic comprehensive evaluation
time orness
time order weighted averaging operator
minimal variability method
