Intelligent expressway pre-maintenance method and system based on artificial neural network

Abstract

The invention relates to an intelligent expressway pre-maintenance method based on an artificial neural network. Theintelligent expressway pre-maintenance method comprises the following steps: step 1,collecting input features and output features of a first layer of artificial neural network; 2, establishing a first-layer artificial neural network, and training and obtaining a neural network modelof a causal relationship between the road condition data and the road damage data; 3, establishing a second-layer decision tree model; 4, optimizing an algorithm formed by two layers of neural network models with time sequences from the road condition data to the maintenance decision; and step 5, according to the optimization algorithm in the step 4, obtaining a specification from the pavement damage parameter to the road pre-maintenance decision. According to the invention, the prediction precision, the prediction efficiency and the prediction perspectiveness can be improved.

Description

technical field [0001] The invention belongs to the technical field of road maintenance, and relates to an intelligent expressway maintenance method, in particular to an artificial neural network-based intelligent pre-maintenance method and system for an expressway. Background technique [0002] In order to repair and maintain the highway pavement, the pavement maintenance management department of our country not only consumes a lot of manpower but also consumes a lot of financial resources. Adjust the previous pavement maintenance method, from the previous maintenance method of repairing the pavement after damage to the preventive maintenance of the pavement, slow down the damage of the pavement, and reduce the waste of manpower and funds for pavement maintenance. [0003] For the traditional expressway maintenance, it has not yet become a system. For the annual road routine monitoring and monitoring of special road sections, image analysis, index calculation and evaluation...

AI Technical Summary

Problems solved by technology

[0003] For the traditional expressway maintenance, it has not yet become a system. For the annual road routine monitoring and monitoring of special road sections, image analysis, index calculation and evaluation often have a lag; for the recorded data to be stored separately, there is no special Systematic and organized data storage platform, the old data is easy to lose, and it is difficult to export the data; the analysis data method is traditional, the accuracy is not high, the consideration is single, and there is no accurate local pre-maintenance specification to follow

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