Research On Multi-Criteria Decision-Making Based On Clustering With Hard-to-Know Weights

Multi-criteria-decision-making theory and method are widely used in the research of land use efficiency,but the decision-making method used is rough in the calculation of index weight,and it is difficult to divide the results into levels,especially when the weight is difficult to be known.The multi-criteria-decision-making method combined with cluster analysis is unique in the study of land use efficiency and has been adopted by many scholars.However,the clustering process also needs to integrate the weight values.When the weight is difficult to be known,it is necessary to find another way.Weight contains human information,and the intuitive expression of human information is preference information,which is the preference sequence of decision indicators,so preference order can be used to replace weight.Poset theory can solve the problem of preference order calculation,and can also be competent in the decision-making field of cluster analysis using preference order.Based on this,aiming at the problem that the traditional research methods can not solve the decision-making problem when the weight is difficult to obtain,and it is difficult to show the hierarchical relationship of the optimal solution set,a multi-criteria-decision-making method integrating preference order is proposed.Firstly,under the traditional theoretical framework,it is difficult to quickly calculate the preference order,and only the weight value can be obtained.In view of this disadvantage,a method of calculating the preference order based on the partial order stack matrix is proposed.According to the expert judgment matrix,all samples are fused to generate the partial order stack matrix,calculate the Haase matrix,and then obtain the preference order.When constructing a poset and realizing multi-criteria-decision-making,we need to consider the distribution of data.For the data with irregular distribution,we can not simply use dimensionless data to construct a poset,and it is more reliable to construct a poset with index order for decision-making.Secondly,the clustering analysis used in the traditional multi-criteria-decision-making research determines the relationship between relatives and relatives by distance.Aiming at the need to calculate the distance between all samples in the traditional clustering,a multi-criteria-decision-making method based on poset to realize supervised learning clustering is proposed.Taking the mature data set as the sample,a better decision-making effect is obtained;Aiming at the difficulty of predicting the number of types of traditional partitioned clustering,a multi-criteria-decision-making method based on poset to realize unsupervised learning clustering is proposed,which can not only effectively obtain the number of clusters,but also quickly realize clustering analysis;In view of the difficulty of realizing the hierarchical structure of traditional multi-criteria-decision-making results,a multi-criteria-decision-making method based on hierarchical clustering based on poset is proposed,which can effectively show the hierarchical relationship of the optimal solution set and provide a better decision-making basis for decision-makers.The proposed methods are progressive layer by layer,that is,from preliminary exploration to confirmation,and each method needs the support of the preamble chapters.Finally,the proposed multi-criteria-decision-making method is applied to the study of land use efficiency.Taking Fuxin above designated enterprises as an example,it has achieved good results and can be used as the decision-making basis of relevant departments.Through the analysis of clustering results and correlation analysis,it is concluded that the determinants of land use efficiency in different industries are different.Some industries mainly depend on the size of the use area.The larger the area,the lower the general efficiency.At the same time,the land use efficiency has little relationship with several indicators such as fixed assets,main operating income,building density and tax.The land use efficiency of some industries mainly depends on the construction area,main income and tax.The larger the construction scale,the higher the main income and tax,the land use efficiency of enterprises will be higher than that of enterprises with small construction scale,low main income and tax.At the same time,the land use efficiency of such industries has little relationship with indicators such as fixed asset investment and land area.The results fully show that the proposed method is more suitable for the study of land use efficiency,and can also be applied to other research fields.