考虑评价信息满意度的群体信息集结方法研究
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摘要
信息集结方法是群体评价的重要研究内容,针对该问题本文对评价信息满意度进行测度,并基于此对群体信息的集结方法展开研究。该方法根据指标信息的变化赋予评价者不同的权重,以改变现有研究中评价者权重大多固定不变的做法,旨在使群体信息集结的结果更加公正和准确。首先对问题进行界定并给出评价信息满意度的定义;然后分别给出先验信息满意度和评价过程中的信息满意度的确定方法,利用先验信息满意度确定各评价者的初始权重,并利用评价过程中的信息满意度对其修正,从而得到各评价者的权重矩阵。最后,按照各评价者的评价信息满意度对群体评价信息进行集结。
Information aggregation method is an important research in group evaluation. This paper proposes a method to determine the satisfaction degree of group evaluation information,and further researches a group information aggregation method. In order to further improve the fairness and accuracy,a different weight instead of a fixed one is placed on each index from the same expert in this method. Firstly,the evaluation situation and question are developed,and the satisfaction degree of the evaluation information is defined. Secondly,the methods to determine the satisfaction degree of priori information and the one of current information are presented respectively. The former is used to determine initial weights of experts,and the latter is used to modify those weights. A weight matrix of every expert can be determined in this process. Finally,the final aggregation result of group information is obtained by using these weight matrixes.
Information aggregation method is an important research in group evaluation. This paper proposes a method to determine the satisfaction degree of group evaluation information,and further researches a group information aggregation method. In order to further improve the fairness and accuracy,a different weight instead of a fixed one is placed on each index from the same expert in this method. Firstly,the evaluation situation and question are developed,and the satisfaction degree of the evaluation information is defined. Secondly,the methods to determine the satisfaction degree of priori information and the one of current information are presented respectively. The former is used to determine initial weights of experts,and the latter is used to modify those weights. A weight matrix of every expert can be determined in this process. Finally,the final aggregation result of group information is obtained by using these weight matrixes.
引文
[1]郭亚军.综合评价理论、方法及应用[M].北京:科学出版社,2007.
[2] Xian S,Zhang J,Xue W. Fuzzy linguistic induced generalized OWA operator and its application in fuzzy linguistic decision making[J]. International Journal of Intelligent Systems,2016,31(8):749-762.
[3] He X,Wu Y,Yu D,et al. Exploring the ordered weighted averaging operator knowledge domain:a bibliometric analysis[J]. International Journal of Intelligent Systems,2017,32(11):1151-1166.
[4] Kim E Y,Ahn B S. Implicit elicitation of attitudinal character in the OWA operator[J]. International Journal of Intelligent Systems,2018,33(2):281-287.
[5]Lukasz Gadomer,Sosnowski Z A. Knowledge aggregation in decision-making process with c-fuzzy random forest using OWA operators[J]. Soft Computing,2018(2):1-15.
[6]易平涛,李伟伟.诱导密度算子及其性质分析[J].系统管理学报,2011,20(5):527-532.
[7]易平涛,李伟伟,郭亚军.二元语义密度算子及其在多属性决策中的应用[J].控制与决策,2012,27(5):757-760.
[8]张发明,郭亚军,易平涛.基于二维密度加权算子的群体评价信息集结方法[J].系统管理学报,2009,18(4):397-401.
[9]易平涛.多源信息密度集结算子理论及应用[M].北京:科学出版社,2012.
[10]焦波,黄赪东,黄飞,李伟.一种基于最优可能满意度的群AHP判断矩阵集结方法[J].控制与决策,2013,28(8):1242-1246.
[11]李磊,李静,李彤.专家判断矩阵集结的一种最优方法[J].系统工程,2016(9):120-127.
[12]姚升保,李武.群决策中两类区间数判断矩阵的集结方法研究[J].中国管理科学,2015,23(s1):47-51.
[13]张仲敏,李俊山,宋凭,杨亚威.一种基于群组判断离差的偏好集结方法[J].控制与决策,2015,30(11):1960-1966.
[14]吴志彬,徐雷.两种基于个体偏好集结的多属性群决策共识方法[J].控制与决策,2014,29(3):487-493.
[15]郭亚军,姚远,易平涛.一种动态综合评价方法及应用[J].系统工程理论与实践,2007,27(10):154-158.
[2] Xian S,Zhang J,Xue W. Fuzzy linguistic induced generalized OWA operator and its application in fuzzy linguistic decision making[J]. International Journal of Intelligent Systems,2016,31(8):749-762.
[3] He X,Wu Y,Yu D,et al. Exploring the ordered weighted averaging operator knowledge domain:a bibliometric analysis[J]. International Journal of Intelligent Systems,2017,32(11):1151-1166.
[4] Kim E Y,Ahn B S. Implicit elicitation of attitudinal character in the OWA operator[J]. International Journal of Intelligent Systems,2018,33(2):281-287.
[5]Lukasz Gadomer,Sosnowski Z A. Knowledge aggregation in decision-making process with c-fuzzy random forest using OWA operators[J]. Soft Computing,2018(2):1-15.
[6]易平涛,李伟伟.诱导密度算子及其性质分析[J].系统管理学报,2011,20(5):527-532.
[7]易平涛,李伟伟,郭亚军.二元语义密度算子及其在多属性决策中的应用[J].控制与决策,2012,27(5):757-760.
[8]张发明,郭亚军,易平涛.基于二维密度加权算子的群体评价信息集结方法[J].系统管理学报,2009,18(4):397-401.
[9]易平涛.多源信息密度集结算子理论及应用[M].北京:科学出版社,2012.
[10]焦波,黄赪东,黄飞,李伟.一种基于最优可能满意度的群AHP判断矩阵集结方法[J].控制与决策,2013,28(8):1242-1246.
[11]李磊,李静,李彤.专家判断矩阵集结的一种最优方法[J].系统工程,2016(9):120-127.
[12]姚升保,李武.群决策中两类区间数判断矩阵的集结方法研究[J].中国管理科学,2015,23(s1):47-51.
[13]张仲敏,李俊山,宋凭,杨亚威.一种基于群组判断离差的偏好集结方法[J].控制与决策,2015,30(11):1960-1966.
[14]吴志彬,徐雷.两种基于个体偏好集结的多属性群决策共识方法[J].控制与决策,2014,29(3):487-493.
[15]郭亚军,姚远,易平涛.一种动态综合评价方法及应用[J].系统工程理论与实践,2007,27(10):154-158.