Research On Intelligent Generation Of Road Construction Plan Based On CBR

Our country has made great achievements in road construction in recent years,but the traffic pressure has continued to increase.While striding forward to the goal of being a "transportation power",our country has published a number of documents for the informatization and automation of the civil engineering industry.The road construction plan is an indispensable guidance document for each road project in terms of technology and organization.At present,its traditional experience preparation method has a lot of room for improvement.This thesis used case-based reasoning technology to quickly and intelligently generate road construction plans,and used cloud reasoning,Bayesian networks and other theories to take a number of optimization measures in case retrieval and plan application.The main research contents were as follows:(1)Analyzed the knowledge characteristics of road construction technology and the content of road construction plans,and decomposed the knowledge of road construction plans into two parts: case characteristics and solutions.Then,according to the technical needs of CBR,the data storage form of each sub-index was proposed and the value range was explained,forming a complete road construction plan case library structure.(2)In the case retrieval process,the KNN(K-Nearest Neibghor)algorithm was used to calculate the similarity between cases,and a reasonable calculation method was proposed for the calculation of various types of data spacing.Then a weight optimization method based on two-dimensional cloud reasoning was proposed to weaken the influence of fuzzy input values in case retrieval,and realized the intelligent generation of the entire road construction plan.In the application process after the program output,this thesis constructed a road quality risk Bayesian network,analyzed the road quality risk-related issues based on on-site information,and determined the improvement target of the generated program.(3)By taking a completed highway project in a southern city as an example,constructed a case database and used CBR technology to quickly retrieve the most similar cases,amended to obtain a better construction plan.Then,two-dimensional cloud inference technology was used to optimize the attribute weights in the KNN algorithm,and the case similarity calculation results that were more suitable for the actual characteristics of the case were obtained.Finally,through the risk Bayesian network,the relevant quality inspection data during the construction of the original plan was used to calculate the key quality concern indicators before the construction of the project,the quality risk in the process,and the improvement direction of the original plan was determined.The results showed that the chapters to be improved in the original plan of the project were basically the same as the chapters on the optimization of the CBR generation plan.Based on actual engineering cases,this thesis proves the feasibility and applicability of the intelligent generation method of road construction plan based on CBR,and provides new ideas for the automation of road construction plan preparation and improvement of plan application effects.