Research On Indicator Selection And Evaluation Of Late Support Effect Of Large And Medium-Sized Reservoir Resettlers

The construction of water conservancy and hydropower projects inevitably produced a large number of reservoir resettlers.In order to help resettlers in large and medium-sized reservoirs to restore and improve their production and living conditions,the state has introduced various late support policies and established a late support monitoring and evaluation mechanism.The implementation effect of the late support policy of reservoir resettlers is related to social stability and people’s livelihood and wellbeing,and it needs to be studied and discussed in depth.At the present,there is a lack of standardized and unified standards for the evaluation of the late support effect of reservoir resettlers.When selecting evaluation indicators,the process of selection lacks objectivity,and the evaluation indicators have the problems of strong subjectivity,little impact on evaluation results,and duplication of information.In the evaluation of the effect,most of the evaluation process is biased to qualitative analysis.Therefore,how to systematically and objectively select the evaluation indicators,and use reasonable and accurate evaluation models to comprehensively evaluate the implementation effect of the late support policy of reservoir resettlers,is of great significance to further update and improve support policies and ensure the livelihood of resettlers.Firstly,this paper studies the evaluation indicators based on the principles of comprehensive,systematic and independent,and constructs a pre-selection index system for evaluating the late support effect of large and medium-sized reservoir resettlers.By combining grey variable weight clustering,multiple correlation analysis and cumulative information contribution rate,the selection of indicators is completed,and qualitative analysis and quantitative statistics are combined.A set of relatively objective and complete evaluation index system is determined.Secondly,multi-factor indicators are taken as variables,subjective weights are measured by hierarchical weighting method,and objective weights are measured by entropy weighting method.An optimal solution model of index combination weighting based on game theory is established to obtain the combination weights and achieve the "optimization" of index weights.Then,in the comprehensive evaluation,the central point triangle whitening weight function is introduced as the middle class function to improve the mathematical model of the traditional gray whitening weight function,which overcomes the defect of the unreasonable selection of the end points of the traditional method.The two-stage decision method is introduced to the grey clustering judgment,which avoids the problem that the maximum clustering coefficient of the traditional clustering evaluation has no significant difference.Finally,taking the monitoring and evaluation of the implementation effect of late support policies of 2020-2021 in Shaanxi Province as an engineering example,an evaluation model based on grey whitening weight function clustering was established for empirical evaluation.Through comparative analysis,it is found that the evaluation results of this paper are consistent with the actual situation,which verifies the rationality and reliability of the model,and can provide reference for the evaluation of the late support effect of reservoir resettlers and other related evaluation work.