Application In The Comprehensive Evaluation Of Density Operator With Encouragement And Chastisement Function

Having broad application prospects, comprehensive evaluation is objective, fair and reasonable overall assessment made to the evaluation objects. Classic comprehensive evaluation process includes establishing evaluation index system, index pretreatment, determining the index weight and evaluation information aggregation. Aggregation of evaluation information is an important link. At the moment the common methods to aggregating information include methods based on the function of index values, based on the index position and based on index distribution. Commonly used operators include arithmetic average (AA) operator, geometric average (GA) operator, maximum (Max) operator, the minimum (Min) operator, the median operator, mode operator, and weighted arithmetic average (WAA) operator, weighted geometric arithmetic average operator (WGA) operator and the ordered weighted averaging (OWA) operator.Different from the above operators, middle density weighted average (DWA) operator consider the characteristics of density data itself, as taken widely attention to. In this paper, according to the characteristics of density operator itself, it can be used in the personnel appraisal and has important application value for personnel selection. Based on this proposing the comprehensive evaluation of density operator with encouragement and chastisement function, it is to expand application field of the density operator in personnel selection. Different from the statically one-off weighting in the past, the operator takes statically quadratic weighting method. At the same time the operator does not consider the weight of evaluation indexes. Through the index of information empowerment, it can avoid expecting to the evaluation indexes and taking a shortcut to result in deformity development due to often using one-off weighting method.The main research works of this paper are as follows:(1)Based on the characteristics of the density operator, the paper has built a disciplinary characteristics of the density operator. First of all, according to the experience of the testee’s disciplinary and attitude, determine the number of level of rewards and punishments, rewards and punishment factor, and to the entire data range partition level of rewards and punishments; Second, determine the level of the weight. Introduction of disciplinary attitude factor, according to the different levels of density, determine the weight with different levels of rewards and punishments; Finally, fall into different levels of each parameter values, through the corresponding contribution value or loss value to determine the weight of each index, and to rally the entire result.(2)Research on different hierarchy method affecting the final evaluation results. Use the average division, increasing, decreasing ladder, reflecting "middle big on both small sides" and reflecting "middle small on both big sides" division methods, to explain the density operator model with encouragement and chastisement function. Analysis and comparison, summed up the characteristics of different partition methods.(3)Research on affect of the evaluators of attitude to the final evaluation results. Sensitivity analysis about the rewards and punishment factors in different divided into encouragement and chastisement grade methods. Use matlab software to simulate, obtaining the result of reflection on different divided into encouragement and chastisement grade methods.