Research On Online Evaluation Group Decision Making Method Under Large Group

Today in the information age,network technology continues to develop,and more and more people in their lives begin to use some network information to solve or deal with some of the problems that require decision-making in work and life.The decision-making of the problem also began to use online evaluation to make the method of decision-making more convenient.At the same time,due to the large number of participants,the resolution of decision-making problems has become more and more complex.Not only needs to consider more aspects,but also need to invite experts to participate,so that the problem solving involving the public and experts guarantees the decision-making.The result is more objective,scientific and universally applicable.This paper conducts research based on the online evaluation group decision-making of the public group,so that the public group and experts participate in the group decision-making process through online evaluation,and allow the public and experts to express evaluation information in a variety of ways to make the expression of evaluation information easier and more convenient,as well as more accurate and more real.The contents in this thesis includes the following three parts:Firstly,the details of methods and theoretical knowledge are analyzed in this part,which are involved in the multi-attribute group decision-making problems,and the backgrounds of the group decision-making problems are also introduced,as well as the definition and applications of fuzzy set theory.At the same time,the fuzzy reciprocal preference relationship and two-tuple semantics are explained,which are used in processing the evaluation information,and the definition of attribute weights in decision-making problems and the main methods of determining weights are discussed too.Secondly,by means of setting the reference language fuzzy set and two-tuple semantics,the evaluation information of the public are normalized.In addition,the t6 evaluation information experts are normalized based on the fuzzy reciprocal preference relationship;on the basis of the standardized evaluation information,a model is established to obtain the objective weight of the attribute,by maximizing the deviation and the method of entropy;the model is established to obtain the subjective weight of the attribute by the principle of minimum distance;the subjective and objective comprehensive weights of the attributes is obtained by combining multiplicative combination weighting and additive combination weighting,the overall values of the alternatives are obtained by integrating,and an example is used to illustrate the feasibility of the above-mentioned research method.Finally,in order to better display the research method of this thesis,a general online evaluation system is designed.The online evaluation system is logged by the public,experts,and administrators,by which problems are evaluated and decision-making results are calculated,while the evaluation data is saved through a database to facilitate later data processing.