基于游线调度的洞窟微环境调节技术研究

发布时间：2018-01-03 07:02

本文关键词：基于游线调度的洞窟微环境调节技术研究　出处：《浙江大学》2017年硕士论文　论文类型：学位论文

更多相关文章： CO_2 游客参观 游线调度 莫高窟 模拟

【摘要】：莫高窟坐落于敦煌市东南的鸣沙山上,以精妙的壁画与精湛的塑像闻名于世。旅游业的迅速发展带来了巨大的经济效益,同时给莫高窟的保护和管理工作带来了许多难题。莫高窟虽然规模宏大,但适用于对外开放的洞窟数量不多,可承载的游客容量有限;由于各个洞窟环境封闭,游客进入洞窟内参观会产生二氧化碳和水汽,影响洞窟内的微环境。若洞窟长期处于不适的微环境中,会加剧洞内壁画和雕塑的褪色甚至发生起甲、龟裂乃至脱落。为了尽量降低旅游开放给莫高窟洞窟微环境带来的负面影响,论文研究了基于游线调度的洞窟微环境调节技术。论文首先研究了适用于莫高窟的洞窟二氧化碳浓度变化模型,该模型定量地描述了游客流量如何影响洞窟二氧化碳浓度变化。二氧化碳作为洞窟主要的微环境指标,研究窟内二氧化碳浓度随游客流量的变化模型对制定游线调度策略具有指导性的意义。论文分析了无游客参观情况下洞窟二氧化碳浓度的变化模型,并根据游客参观的实际情况对原有模型进行了改进。然后,论文基于莫高窟现有游客管理策略提出了游客分组参观模拟算法。莫高窟工作人员将大约20个游客作为一个游客分组,给其分配了一条游览路线,由讲解员带队进行参观。游客分组参观模拟算法根据当前景区内所有游客分组的游览现状,模拟所有游客分组未来一段时间的游览行为。通过模拟游客分组在景区内的游览行为,一方面可以为游客分组选择尽可能与其他游客分组的游览计划不冲突的路线,另一方面可以计算游客分组选择不同的游线对景区的环境带来的不同影响,最后权衡二者之间的利弊,选择合理的游览路线。论文基于现有的游线调度算法框架,提出了基于游线优选模型的游线调度策略,并采用莫高窟历史游客访问记录对几种游线调度策略进行对比。实验表明采用基于游线优选模型的游线调度策略能有效降低洞窟微环境风险。最后,论文设计并实现了游览路线推荐系统。系统基于游客分组参观模拟算法、洞窟二氧化碳浓度变化模型以及基于游线优选模型的调度算法实现了莫高窟景区的游览路线推荐功能。
[Abstract]:Mogao Grottoes is located in Dunhuang City, Southeast of the Mingsha mountains, is famous for its exquisite exquisite murals and statues. The rapid development of the tourism industry has brought enormous economic benefits, at the same time to Mogao Grottoes's protection and management has brought many problems. Although the Mogao Grottoes grand scale, but the number of applicable to the opening of the cave is not much, the tourists carrying capacity is limited; because each cave closed environment, visitors enter the cave tour will produce carbon dioxide and water vapor. The influence of micro environment inside the cave. The cave in the micro environment if the long-term discomfort, will aggravate the cave murals and sculptures faded even from a crack, and even fall off. In order to minimize the negative impact open to the Mogao Grottoes tourism cave micro environment brings, study tour line scheduling of cave micro climate regulation based on. The thesis firstly studies the suitable caves of Mogao Grottoes At the concentration of CO2 model, the model quantitatively describes the flow of tourists how to influence the concentration of carbon dioxide. The carbon dioxide as the cave cave main micro environment index, change model with the tourist flow of the carbon dioxide concentration slightly has the guiding significance for the development of tour line scheduling strategy. This paper analyzes the change of the concentration of carbon dioxide in cave model of tourists visit the case, and according to the actual situation of the visitors to the original model has been improved. Then, the existing Mogao Grottoes tourists management strategy is put forward based on the tourists visit Mogao Grottoes. Packet simulation algorithm of staff will be about 20 tourists as a tourist group, are allocated to a tour route, the announcer led tourists visit the visit. The packet simulation algorithm according to the present situation of all the tourists visit scenic spots in the current packet, to simulate all the tourists The next time the tour group behavior. Through the tour behavior simulation visitors group in the scenic area, one can choose as far as possible for tourists and other visitors packet packet sightseeing program does not conflict route, on the other hand can affect different computing environment tourists group selection tour line of different scenic spots caused by the final weighing the advantages and disadvantages between the two, reasonable selection of the tour route. The existing scheduling algorithm based on the framework of tour line, proposes a scheduling optimization model of tour line tour line based on strategy, and the historical records of several tourists visit Mogao Grottoes tour line scheduling strategy were compared. The experiments show that using the tour line scheduling strategy optimization model can tour the line to reduce the environmental risk based on micro caves. Finally, this thesis designs and implements the tour route recommendation system. The system simulation algorithm based on grouping of tourists visit the cave, two oxygen The model of carbon concentration change and the scheduling algorithm based on the optimization model of the travel line have realized the tour route recommendation function of the Mogao Grottoes scenic spot.

【学位授予单位】：浙江大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP301.6;K879.2

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