Analysis of the Safety Factors of Municipal Road Undercrossing Existing Bridge Based on Fuzzy Analytic Hierarchy Process Methods

Abstract

Increasing traffic volume and insufficient road lanes often require municipal roads to be reconstructed and expanded. Where a road passes under a bridge, the reconstruction and expansion project will inevitably have an impact on the bridge. To evaluate the safety impact of road engineering projects on bridges, this paper evaluates the safety of the roads and ancillary facilities of highway bridges involved in municipal road engineering projects. Based on a comprehensive analysis of the safety factors of municipal roads undercrossing existing bridges, a fuzzy comprehensive analytic hierarchy process (AHP) evaluation method for the influence of road construction on the safety of existing bridges is proposed. First, AHP is used to select 11 evaluation factors. Second, the target layer, criterion layer, and index layer of evaluation factors are established, then a safety evaluation factor system is formed. The three-scale AHP model is used to determine the weight of assessment indexes. Third, through the fuzzy comprehensive AHP evaluation model, the fuzzy hierarchical comprehensive evaluation is carried out for the safety assessment index system. Finally, the fuzzy comprehensive evaluation method is applied to the engineering example of a municipal road undercrossing an existing expressway bridge. The comprehensive safety evaluation of the existing bridge reflects the practicability and feasibility of the method. It is expected that, with further development, the method will improve the decision-making process in bridge safety assessment systems.

Application of Fuzzy Analytic Hierarchy Process in the Quality Monitoring and Evaluation of College Teachers and the Construction of Index System

“…Fuzzy analytic hierarchy process has been widely used in different fields. In terms of transportation, aiming at the problems existing in safety and reliability of roads and bridges, a new optimization model based on fuzzy analytic hierarchy process theory was proposed in [1]. e model obtains the operation data of different vehicles by using the method of hierarchical analysis, and then imports the corresponding data into the target module.…”

Adopting a Multi-Criteria Decision-Making Approach to Identify Barriers to Electrification of Urban Freight in India

“…By using this method, respondents’ judgments can be improved in their imprecise ranking ( 44 ). The fuzzy approach to decision making features uncertainty and fuzziness, and it is suitable for a wide range of real-world scenarios ( 45 – 48 ). In fuzzy AHP, experts use natural language expressions (e.g., equally important, weakly important) to express their judgments.…”

Empirical Analysis of the Impact of High and New Technology on the Export of Traditional Cultural Industry Based on Random Matrix Theory

“…Based on the function of partial correlation coefficient, applying partial correlation analysis to the time series of export earnings of traditional culture, we can eliminate the common influence factors between any two time series of export earnings of traditional culture and analyze the influence of the common influence factors on the export of these two traditional cultures respectively. e partial correlation matrix is applied to the analysis of the correlation structure of traditional cultural export [15], which can further study the structural characteristics of correlation and the information contained therein. e modern investment field usually contains a large number of investment varieties (denoted as N), and the asset dimension is proportional to the sample observation value T. At this time, using the sample covariance matrix to estimate the overall covariance will produce a large deviation [16]; this is also an important reason to solve the high-dimensional portfolio weight problem caused by MV portfolio outside the sample data.Specifically, as n increases, even when the unit is a general matrix, the eigenvalues of the sample covariance matrix will be far away from them [17].…”