Cause And Effect Analysis Of Multi-objective Bridge Deterioration In Yunnan Province

The topography of Yunnan Province has the characteristics of uneven terrain,high mountains and gullies,so highway bridges have become an indispensable part of the province’s transportation,highway bridges with increased use of time will appear to varying degrees of defects and degradation,thus increasing the safety of people’s lives and property hidden danger.Therefore,by conducting a degradation causal analysis of highway bridges,scientifically supported decision support for bridge construction can be provided.Currently,many methods have been used in the causal analysis of bridge deterioration and to help the cause of bridge construction development.However,there are two problems with the currently available analytical methods.Firstly,most technical approaches only consider attributes related to the health status of the bridge,such as only years of use,only bridge type.A single-objective causal analysis of road bridges for deterioration.Secondly,ignoring the problem that the Apriori association rule mining algorithm generates fewer association rules and no association rules at high support and high confidence levels,as well as more association rules and some misleading association rules at relatively low support and low confidence levels,does not guarantee the quality and reliability of the causal association rules for road bridge deterioration mined by the Apriori algorithm.In response to the above problems,this paper takes the Yunnan road bridge as an example,based on the engineering reality,a multi-target bridge deterioration causal analysis method was established.The method introduces a genetic algorithm and a grey association analysis method based on the Apriori association rule mining algorithm.Firstly,the approach considers the climate associated with the health status of the bridge,including natural disasters such as rainfall,snowfall,and temperature,as well as multiple attributes of the bridge design,construction materials,etc.Secondly,the introduction of genetic algorithms can further streamline the rules mined by the Apriori algorithm and improve the reliability of the rules,and the grey association analysis algorithm transforms complex multi-target genetic algorithm solving problems into single-target solving problems.The experimental data in this paper,provided by Yunnan Provincial Transportation Investment and Construction Group Co.,assesses the causality of bridge deterioration in subtropical areas of Yunnan Province,emphasizing the importance of maintenance and repair.The experimental results show that the age of the bridge,the type of underpass,the form of bridge construction and the construction material,temperature,rainfall and other factors have a greater influence on the deterioration of the bridge.At the same time,by comparison with the method of measuring support and confidence proposed by Qodmanan et al.(Sup_conf).It was found that the traditional method for the first class bridge average Sup_conf is 3.832,the second class bridge average Sup_conf is 3.474,and this method for the first class bridge average Sup_conf is 5.698,the second class bridge average Sup_conf is 5.077,Sup_conf increased by 1.875,1.603,respectively,proved the effectiveness of this method.