Research On Spatial Data Quality Evaluation Based On Hesitant Fuzzy Set

With the rapid development of computer technology and network communication technology,the application field of geographic information system is increasingly extensive.GIS's application and development cannot leave the spatial data,however,in today's era of big data,space becomes especially important to the quality of the data,spatial data quality will directly affect the accuracy of GIS decision in order to improve the quality of spatial data,the paper will start from the uncertainty of spatial data,the fuzzy uncertainty of spatial data,in the original traditional spatial data evaluation methods,combined with hesitation the principle of fuzzy set,using hesitant fuzzy preference relation and multi-attribute evaluation of spatial data quality evaluation,the main research contents are as follows.(1)the research of hesitating fuzzy preference relation in spatial data evaluationBased on the deficiency of the traditional evaluation method in the fuzziness of data quality,a spatial data quality evaluation method based on the hesitating fuzzy set is proposed.the dithering fuzzy preference relation algorithm and dithering product preference relation algorithm were used to evaluate the quality of spatial data preference relation,and the dithering fuzzy preference relation was formed by making all possible preference values for several spatial data products by several expert groups.Then,operator integration is carried out for the hesitating preference relation,score function is calculated and sorted according to the score function.The two evaluation results are compared and analyzed with examples,and the relationship of hesitation preference is verified by using intuitionistic fuzzy preference relation.Research on the consistency of hesitant preference relationship in spatial data quality evaluation Considering the consistency of hesitating preference relation,the iterative algorithm of hesitating preference relation consistency and the algorithm of causative improvement are used to evaluate the quality of spatial data.The consistency of hesitating preference relation is analyzed with an example,and the consistency of intuitionistic fuzzy relation is verified,and the results are compared and analyzed.(2)research on TOPSIS based fuzzy decision making in spatial data evaluationConsidering the quality element of spatial data,TOPSIS method was used to evaluate the weights obtained from the completely unknown attribute weights and expert weights calculated by the model,and the results were analyzed.Experts give possible evaluation values for each attribute of different spatial data products,and their importance is unknown,forming a hesitant fuzzy decision matrix.Through the hesitating fuzzy decision matrix,different algorithms are used to obtain the weight of attributes,and the product ordering results are obtained through the distance measure of hesitating fuzzy elements to select the optimal spatial data product,combined with an example,USES the intuitionistic fuzzy TOPSIS multi-attribute decision algorithm to make a comparative analysis of the hesitant fuzzy TOPSIS multi-attribute decision algorithm.(3)research on spatial data quality evaluation based on HF ELECTREConsidering that when seeking a consistent solution in the process of group decision-making,the introduction of hesitating and fuzzy elements can avoid forcing the average preference of group members,the HF EL ECTRE method is introduced to evaluate the quality of spatial data.In this paper,we use the ELECTRE I and ELECTRE II in ELECTRE method to evaluate,the method is by scoring function and bias function get hesitant fuzzy consistent matrix and fuzzy not hesitate-matrix,and then construct integrated dominant matrices,finally draw level priority and get the optimal evaluation scheme,combined with the instance will be intuitionistic fuzzy multiple attribute decision making based on projection model of the evaluation results with HF-it is the result of EL ECTRE method were analyzed.The evaluation of spatial data quality based on hesitating fuzzy sets is an important extension of the evaluation of the existing spatial data quality,which improves the defect of missing information in the evaluation process to a great extent and improves the accuracy of the evaluation.Therefore,the evaluation method based on hesitating fuzzy sets is scientific and reasonable.