CAJ | 학술논문

为了提高高速公路应急预案匹配的智能性和实时性，引入了人工智能领域中的范例推理技术（CBR）并提出一种模糊匹配方法作为其检索算法。该方法结合最大隶属度原则确定突发事件和案例库中各个案例定量描述属性所属的模糊集，利用格贴近度计算突发事件与案例对应各属性之间的相似程度，结合权重选择出相似度最大的案例作为预案。通过与现有匹配算法的对比，体现出模糊匹配算法能有效的处理模糊性而在交通应急预案匹配中的优越性，是一种可行的应急预案智能匹配方法。
위료제고고속공로응급예안필배적지능성화실시성，인입료인공지능영역중적범례추리기술（CBR）병제출일충모호필배방법작위기검색산법。해방법결합최대대속도원칙학정돌발사건화안례고중각개안례정량묘술속성소속적모호집，이용격첩근도계산돌발사건여안례대응각속성지간적상사정도，결합권중선택출상사도최대적안례작위예안。통과여현유필배산법적대비，체현출모호필배산법능유효적처리모호성이재교통응급예안필배중적우월성，시일충가행적응급예안지능필배방법。
In order to improve the inteI igence and reaI-time of traffic emergency prepIan matching,this paper presents case-based reasoning technoIogy in the fieId of artificiaI inteI igence and proposes a fuzzy matching method as its search aIgo-rithm.In the method,quantitative attributes of emergency and cases are identified to fuzzy sets based on the principIe of maximum degree of membership.The cIose degree between emergency and cases can be caIcuIated with weights and simiIarity between attributes.By comparison with the existing matching aIgorithms,it reveaIs the superiority of fuzzy matching on traffic emergency prepIan matching because of deaIing with ambiguity effectiveIy.