The Linguistic Truth-valued Intuitionistic Fuzzy Decision Making Method And Its Application In Mooc Intelligent Selection System

As for decision making problems in the real world,more and more people prefer to use linguistic values to evaluate attributes.Traditional linguistic values are chained and comparable,however,incomparable linguistic values often appear in real life.And traditional method requires to translate from linguistic values into numeric values,but because linguistic values are different from the numerical characteristics,which will cause the lack of information.The paper uses linguistic truth-valued intuitionistic fuzzy pairs to express linguistic-valued information which is both comparable and incomparable,which can calculate linguistic values directly and avoid the loss of information.Based on the linguistic truth-valued intuitionistic fuzzy lattice,the paper deeply studies multi-attribute decisions with linguistic-valued information and establishes a MOOC intelligent selection system.The main results as follows:(1)The paper establishes a linguistic truth-valued intuitionistic fuzzy multi-attribute decision making method based on TOPSIS.Firstly,normalized distance algorithm and positive and negative ideal point between linguistic truth-valued intuitionistic fuzzy pairs are proposed.Secondly,we obtain the relative degree of closeness between each alternative with ideal points by calculating the distances between the attribute values of alternatives with ideal points.Finally,comes out the best choice according to the ranking result.Take the learner to choose a mobile learning application as an example,and through the comparision analysis shows the reasonability of the proposed method.(2)The paper establishes a multi-attribute group decision making method based on the linguistic truth-valued intuitionistic fuzzy aggregation operators.Firstly,for the aggregation problem of linguistic-valued evaluation information,linguistic truth-valued intuitionistic fuzzy weighted averaging operator(LTV-IFWA)and linguistic truth-valued intuitionistic fuzzy ordered weighted averaging operator(LTV-IFOWA)are proposed.Thereinto,LTV-IFWA is used to aggregate attribute evaluation values of each alternative provided by experts,and get the integrated attribute values.Then we get the group integrated attribute values of each alternative by aggregating the integrated attribute values on LTV-IFOWA.Secondly,according to the rankind result of group integrated attribute values,the best alternative is selected.For the incomparable situation in the ranking process,reference nearness degree is presented.The algorithms of partial true reference nearness degree(?_T)and partial false reference nearness degree(?_F)are given,and the decision makers can select algorithm by preference.Finally,take the choice of excellent teachers as an example,and through the comparision analysis to illustrate the reasonability of the proposed method.(3)Two kinds of linguistic truth-valued intuitionistic fuzzy decision making methods are applied into the MOOC intelligent selection system.In the MOOC platforms,a number of colleges have provided MOOCs which are the same course,how to choose the most suitable one from them is an important issue.Firstly,this paper establishes a MOOC quality evaluation indicator system.Then we construct a MOOC intelligent selection system by linguistic truth-valued intuitionistic fuzzy decision making methods provided by the paper.The system can help learners intelligently choose the most suitable one,which is of great significance to its knowledge internalization.