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F-AMST模型构建及其在旅游集聚区划分中的应用

Modelling and Application of Fuzzy Adaptive Minimum Spanning Tree in Tourism Agglomeration Area Division

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【作者】 高伟路紫张秋娈白龙

【Author】 GAO Wei;LU Zi;ZHANG Qiu-luan;BAI Long;School of Resource and Environment Sciences,Hebei Normal University;

【通讯作者】 路紫;

【机构】 河北师范大学资源与环境科学学院

【摘要】 本文基于自适应最小生成树方法和模糊分级评判方法构建了由三层次组成的模糊-自适应最小生成树(F-AMST)模型,并将河北省山区全部A级景区节点划分为8个旅游集聚区。研究发现:(1)景区节点间时空距离与其模糊集聚程度呈强负相关性,旅游集聚区的模糊集聚程度大小:凝聚型>随机型>均匀型。(2)景区节点等级系统优劣与其模糊集聚程度存在弱正相关性,多数具有5A级景区节点的旅游集聚区在加入景区节点等级因素后,其模糊集聚程度的位序普遍有所提高。(3)景区节点间时空距离与其等级系统优劣并未明显相关性。

【Abstract】 A fuzzy adaptive minimum spanning tree(F-AMST) model composed of three levels is proposed in this study. This model is based on adaptive minimum spanning tree method and fuzzy level evaluation method. All the A-level scenic spots in mountain areas of Hebei province are divided into 8 tourism agglomeration areas. It shows:(1)There is a strongly negative correlation between spatio-temporal distance and fuzzy agglomeration degree. Fuzzy agglomeration degree of tourism agglomeration area is: aggregated pattern > stochastic pattern > uniform pattern.(2)There is a weak positive correlation between hierarchical system of scenic spots and fuzzy agglomeration degree. When a tourism agglomeration area with 5 A scenic spots is added to the hierarchical system of scenic spots, the order of fuzzy agglomeration degree is generally improved.(3)There is no obvious correlation between spatio-temporal distance and hierarchical system of scenic spots.

【基金】 国家自然科学基金资助项目(41671121);河北省科技厅软科学项目(16236004D)
  • 【文献出处】 模糊系统与数学 ,Fuzzy Systems and Mathematics , 编辑部邮箱 ,2019年04期
  • 【分类号】F592.7
  • 【下载频次】42
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