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基于人工神经网络的京西古村落民俗旅游资源评价    

Evaluation on Folk Tourism Resources of Ancient Village in West Beijing Based on Artificial Neural Network

文献类型:期刊文献

中文题名:基于人工神经网络的京西古村落民俗旅游资源评价

英文题名:Evaluation on Folk Tourism Resources of Ancient Village in West Beijing Based on Artificial Neural Network

作者:时少华[1]

第一作者:时少华

机构:[1]北京联合大学旅游学院

第一机构:北京联合大学旅游学院

年份:2015

卷号:54

期号:12

起止页码:3048-3054

中文期刊名:湖北农业科学

外文期刊名:Hubei Agricultural Sciences

收录:CSTPCD

基金:北京市优秀人才培养项目(2013D005022000009);北京联合大学人才强校计划项目(BPHR2012E03)

语种:中文

中文关键词:人工神经网络;京西古村落;民俗旅游资源;评价

外文关键词:artificial neural network; ancient village of west Beijing; folk tourism resources; evaluation

摘要:对古村落民俗旅游资源进行评价可以促进民俗旅游的健康可持续发展。以北京西部的门头沟区8个传统村落为研究对象,在评价指标体系基础上运用Clementine12.0中人工神经网络的快速、动态和RBFN 3种评价模型进行仿真训练;在动态方法模型基础上结合模糊综合评价方法对8个古村落民俗旅游资源情况进行评价。结果表明,人工神经网络中的动态模型较其他两种模型可信度更高;8个古村落民俗旅游资源整体状况中等偏上,民俗资源还需进一步开发利用。建议深层次挖掘民俗资源蕴涵的历史和文化内涵、科学系统规划利用、提高交通便利性和基础设施建设,进一步提升京西民俗旅游资源可持续利用程度。
Evaluation on folk tourism resources of a ncient village can promote healthy and sustainable development of folk tourism. Taking eight traditional villages of Mentougou in west Beijing as research subject, on the basis of the evaluation index system, three evaluation models-fast,dynamic and RBFN of the artifical neural network in Clenentine12.0 were simulated; and based on the method of dynamic model combined with the method of fuzzy comprehensive evaluation, the situation of folk tourism resources in eight ancient villages was evaluated. Results showed that dynamic model owned higher credibility than two other models in artificial neural network, and the overall situation of folk tourism resources in eight traditional villages was above the average, therefore folk tourism resources still need futher development and utilization. It was suggested to deep excavate the history and culture connotation of folk resources, to conduce systematically and plan scientifically, to improve the traffic convenience and infrastructure, and to further enhance the degree of sustainable utilization of the folk tourism resources of west Beijing.

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