Highway intelligent route selection method in permafrost region of Qinghai-Tibet Plateau
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摘要: 为解决传统公路选线方法难以完全考虑青藏高原多年冻土区复杂地理环境的问题, 将地理信息系统(GIS)的空间数据分析技术与智能进化算法引入到多年冻土区的公路选线过程中。利用GIS进行青藏高原多年冻土区的空间数据挖掘, 从冻土病害影响因子的连续度和发育度方面考虑多年冻土区微地貌对公路选线的影响, 建立了冻土病害危险度计算模型。利用面向对象技术开发组件式GIS, 应用于青藏高原多年冻土区, 完成了对多年冻土区复杂地理信息的分析和提取。构建了线位优化遗传算法, 确立了自适应的迭代策略, 借助粒子群算法, 建立了基于遗传算法的路线优化模型。以青藏高原西大滩至昆仑山口路线走廊带某路段为例, 进行了公路智能选线研究, 经算法多次迭代后, 得到了最优的线位方案。研究结果表明: 在实际环境数据试验中, 遗传算法在迭代至第60代左右时得到危险度最低的优选方案, 其综合危险度稳定在3.75左右。可见, 青藏高原多年冻土区公路智能选线方法能够结合各类冻土病害的危险程度, 为公路线位布局指明冻土病害影响较小的区域, 有效兼顾了“主动保护多年冻土, 确保路基稳定, 生态环境友好, 布局经济合理”等要求, 可作为多年冻土区公路路线设计的参考方法。Abstract: To solve the problem that traditional highway route selection method can not fully consider the complex geographical environment in the permafrost region of Qinghai-Tibet Plateau, the spatial data analysis technology of geographic information system(GIS)and intelligent evolutionary algorithm were introduced into the highway route selection process in permafrost region. The spatial data mining in the permafrost region of Qinghai-Tibet Plateau was finished by using GIS, the influence of the microtopography of the permafrost region on highway route selection was considered from the continuity degree and development degree of the influence factors of frozen soil diseases, and the risk degree calculation model of frozen soil disease was established. The component GIS was developed by using object-oriented components technology, and then applied in the permafrost region of Qinghai-Tibet Plateau, so the analysis and extraction of complex geographic information in the permafrost region were completed. The route optimization genetic algorithm and the adaptive iterative method were established, and with the aid of particle swarm algorithm, the route optimization model was set up based on the genetic algorithm. A road section of the route corridor of Qinghai-Tibet Plateau between Xidatan and Kunlun Mountains pass was selected as an example, and the highway intelligent route selection was researched, and the final route position scheme was obtained. Analysis result shows that in the experiment based on real environmental data, the optimal scheme with the least of risk degree is obtained after about 60 th iteration, and the risk degree is stable at about 3. 75. So the intelligent route selection method in the permafrost region of Qinghai-Tibet Plateau can combine the risk of all kinds of frozen soil diseases, and specify the area with less impact of frozen soil disease for highway layout. The optimized scheme effectively takes into account the "initiative protecting permafrost, ensuring the stability of roadbed, friendly ecological environment, economic-reasonable layout"requirements, and can be used as the reference method for highway route design in the permafrost region.
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图 6 青藏高原多年冻土区危险度识别结果
Figure 6. Risk degree identification result of permafrost region result of Qinghai-Tibet Plateau
表 1 判断矩阵的一般形式
Table 1. General form of judgment matrix
表 2 随机一致性指标取值
Table 2. Values of random coincidence index
表 3 准则层1中各因素的判断矩阵
Table 3. Judgment matrix of factors in criterion layer 1
表 4 准则层1中各因素的相对权重
Table 4. Relative weights of factors in criterion layer 1
表 5 危险度函数中的权重
Table 5. Weights of risk degree function
表 6 准则层2中各因素的判断矩阵
Table 6. Judgment matrix of factors in criterion layer 2
表 7 准则层2中各因素的相对权重
Table 7. Relative weights of factors in criterion layer 2
表 8 连续度函数中的权重
Table 8. Weights of continuity degree function
表 9 准则层3中各因素的判断矩阵
Table 9. Judgment matrix of factors in criterion layer 3
表 10 0准则层3中各因素的相对权重
Table 10. Relative weights of factors in criterion layer 3
表 11 1发育度函数中的权重
Table 11. Weights of development degree function
表 12 2不同的标度分值所对应的冻土病害分级
Table 12. Scale classification of frozen soil disease corresponding to different scales scores
表 13 3地块属性值与总危险度
Table 13. Block attribute values and total risk degrees
表 14 4运行指标
Table 14. Operation indexes
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