摘要
复杂地质条件下长大隧道TBM的选型适应性评价决策是一个受多因素影响的不确定及模糊的问题,一般难以抉择,而TBM的合理选型是工程成功的关键。基于案例推理方法可利用已有的工程经验知识来对新遇到的问题进行解答,能够准确高效地对TBM选型适应性进行评价。根据最近邻法,建立TBM选型适应性相似度计算公式,并选取能够充分反映不同机型地质适应性差异、具有代表性及区分度高的7个评价指标,确定7个评价指标的权重。针对TBM选型适应性评价的特点,提出基于案例推理的TBM选型适应性评价决策系统CBR-TBMSAEDS(Case-Based Reasoning-TBM selection adaptive evaluation decision system)的总体设计,开发了CBR-TBMSAEDS。利用该系统对所构建的案例库进行TBM的选型适应性评价,评价结果与实际情况相吻合。
The evaluation and decision on the adaptability of TBM type selection for long tunnels under complex geological conditions is an uncertain and ambiguous problem affected by many factors.It is generally difficult to choose,and the reasonable selection of TBM is the key to the success of the project.Case-based reasoning(CBR)can use the existing engineering experience knowledge to solve the new problems,which can accurately and efficiently evaluate the adaptability of TBM selection.Based on the nearest neighbor method,a formula for calculating the adaptability similarity of TBM selection is established in this paper.Seven evaluation indexes which can fully reflect the difference of geological adaptability of different types are selected,and the weights of seven evaluation indexes are determined.According to the characteristics of TBM selection adaptability evaluation,the overall design of CBR-TBMSAEDS is proposed,and CBR-TBMSAEDS is developed.The system is used to evaluate the adaptability of TBM selection for the case base,and the evaluation results are consistent with the actual situation.
作者
詹金武
李涛
黄建华
孙明社
陈军浩
ZHAN Jinwu;LI Tao;HUANG Jianhua;SUN Mingshe;CHEN Junhao(School of Civil Engineering,Fujian University of Technology,Fuzhou 350118,China;School of Civil Engineering,Beijing Jiaotong University,Beijing 100044,China;Key Laboratory of Underground Engineering,Fujian Province University,Fuzhou 350118,China)
出处
《铁道科学与工程学报》
CAS
CSCD
北大核心
2020年第6期1562-1570,共9页
Journal of Railway Science and Engineering
基金
国家重点基础研究发展计划资助项目(2014CB046906)
福建工程学院科研启动基金资助项目(GY-Z19096)
国家自然科学基金资助项目(41672278)。
关键词
TBM选型
最近邻法
案例推理
相似度
决策系统
TBM selection
nearest neighbor
case-based reasoning
similarity
decision system
