基于Hopfield算法的特色旅游路线设计——以大岭山森林公园为例  

Design of Special Tourism Route Based on Hopfield Algorithm——A case study of Dalingshan Forest Park

作　　者：龚丹丹[1] 吴小芳[1,2] 

机构地区：[1]华南农业大学信息学院,广东广州510642 [2]华南农业大学建设用地再开发国土资源部重点实验室,广东广州510642

出　　处：《绿色科技》2014年第5期254-256,259,共4页Journal of Green Science and Technology

基　　金：广东省教育部产学研结合项目(编号:2012B091100111)资助;华南农业大学2011年教育教学改革与研究项目

摘　　要：针对特色旅游路线的选择问题,提出了使用Hopfield神经网络的算法和优化模型,并结合东莞市大岭山森林公园地图,着重考虑公园景点评分、出入口设置、最短路径等因素,构建了Hopfield神经网络模型。依据该神经网络模型算法,设计了休闲保健、户外体验、花季特色旅游路线,并通过与现实旅游路线相比较,证明了基于Hopfield神经网络算法设计的旅游路线是合理可行的。According to the problem of tourism route design of Dalingshan Forest Park, this article uses Hopfield algorithms and optimization model to build a Hopfield neural nerwork model for Dalingshan Forest Park by considering the scenic spots score, the setup of entrance and exit, and the shortest route of the Park, etc. According to the algorithm of Hopfield neural network,the article designs three special routes including leisure and health tourism route, outdoor experience tourism route, and flower tourism route. By comparing with the actual routes, it is proved that these three routes are reasonable and feasible.

关 键 词：特色旅游路线 HOPFIELD神经网络 森林公园 

分 类 号：S759.91[农业科学—森林经理学]