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作 者:杨征权 吴建国[2] YANG Zhengquan;WU Jianguo(Dazhou Vocational and Technical College,Dazhou 635001,China;Southwest Minzu University,Chengdu 610041,China)
机构地区:[1]达州职业技术学院,四川达州635001 [2]西南民族大学,四川成都610041
出 处:《灾害学》2020年第1期49-54,共6页Journal of Catastrophology
基 金:国家自然科学基金项目(51108394);2016年四川省新农村乡风文明建设研究中心项目(SCXF201621)
摘 要:旅游开发对沙漠化地区的影响是不可避免的,为深入分析旅游开发与沙漠化之间的关系,需进行旅游开发对沙漠化地区沙漠化产生影响的综合评价分析,并构建沙漠化地区沙漠化影响分析模型,模型是由总目标层、综合评价层和因子评价层构成,采用感知等级评价方法评价旅游开发对沙漠化地区沙漠化的影响,通过层次分析法和熵值法获取各层的指标因子权重,提升指标因子可信度;构建综合评价层与因子评价层的模糊综合判断矩阵,采用该矩阵判定指标因子的感知等级,得到指标因子对分析模型总目标层的综合影响分值,依据该分值评估旅游开发对沙漠化地区沙漠化的影响情况。The influence of tourism development on desertification areas is inevitable. In order to deeply analyze the relationship between tourism development and desertification, it is necessary to carry out comprehensive evaluation and analysis of the impact of tourism development on desertification in desertification areas, and construct relevant models. In order to ensure the validity of the model, it is necessary to improve the weight reliability of the evaluation index factor. The model is composed of the total target layer, the comprehensive evaluation layer and the factor evaluation layer, and the model adopts the perceptual grade evaluation method to evaluate the effect of the tourism development on the desertification in the desertification area, and the level analysis method and the entropy method are adopted to obtain the layers. The fuzzy comprehensive judgment matrix of comprehensive evaluation layer and factor evaluation layer is constructed, and the perceptual grade of index factor is determined by using this matrix, and the comprehensive influence score of index factor on the total target layer of the analysis model is obtained, and the influence of overexploitation on desertification in desertification area is evaluated according to the score. The experimental results show that the designed model can effectively analyze the influence of each index factor in overexploitation on desertification in desertification area, and the average evaluation score of analysis accuracy is 98.3, and the fluctuation range of accuracy is 97.1% ≤ 99.0%, which indicates that the model can obtain accurate analysis results.
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