Research On Precision Recognition Method Of Multidimensional Poverty And Its Application

The problem of poverty has been the focus of attention for all walks in the country,and poverty has risen from a single-dimensional to multidimensional problem.With the proposal of accurate poverty alleviation,more and more scholars at home and abroad have focused on the identification of multidimensional poverty.According to recent research and survey results,we find that the proportion of poor people in Western China was significantly higher than that in other areas,especially in mountainous areas.At present,the identification of poverty in China is mostly through the income index and some non-axiomatic methods,which leads to the fact that the expression of poverty is mostly shown through statistical charts.Such recognition technology of poverty can not effectively analyze the level of poverty and poverty causation,so that it fails to help the local government in carrying out accurate poverty alleviation.Because of the focus of the Multidimensional Poverty Theory,the index system related has become the focus of research for students both at home and abroad.But because poverty has regional characteristics and multidimensional complexity of recognition,the establishment of the regional index system and the construction of accurate identification and early warning model is what is significant in accurate poverty alleviation policy.This paper has conducted statistical processing for small indexes on all dimensions of poverty,and undergone formal description and discretization for all the 58 indicators of poverty in Dingxi on all dimension by employing the establishment of index system for multidimensional poverty on the basis of Rough Set,aiming at the problems:the subjectivity and incompleteness of choosing index system for multidimensional poverty,and the lack of dynamic model of identification for multidimensional poverty.Finally,the poverty index system for Dingxi is obtained by using attribution reduction.By establishing matter-element model for multidimensional poverty,extentics dynamic identification methods for multidimensional poverty can be generated on the basis of correlation function.The index system established by employing such dynamic identification model is comprehensive and concise.Moreover,it is able to analyze the future development trend at the same time of evaluating the current level.Finally,taking Dingxi city as an example,an empirical study was conducted based on the data of 2015 from farmers in Dingxi,and index system of circular economy in Dingxi City was established,so as to identify the multidimensional poverty degree and make early warning for six counties and one district in Dingxi.Corresponding suggestions on policy were put forward according to the above results so as to serve the accurate poverty alleviation in Dingxi city.