← Search

Data · dataset · 2025

SPA-IAHP-CRITIC

Listed in ScienceDB

To enhance Expressway's response to sudden accidents and improve maintenance resilience, this paper introduces safety resilience theory into high-speed section maintenance safety management.

Description

Considering highway features and based on resilience theory's five characteristics, key factors for high-speed maintenance safety resilience are identified using Word Frequency Analysis (WFA). The nonlinear mapping between system classification and highway characteristics is pivotal.

Subjective and objective weights of maintenance safety resilience indices are weighted using the Interval Analytic Hierarchy Process Critical (IAHP-CRITICAL) method and Minimum Information Identification Principle, addressing traditional IAHP's fuzziness. The Improved Dung Beetle Algorithm Extreme Learning Machine (DBO-ELM) is employed for comprehensive evaluation. The WFA-CRITICAL-IAHP-DBO-ELM model is applied to a Chang-Zhang Expressway section.

Links

Where it is published

Catalogue records · 1

Topics

Provenance · 1 source records, 10 field assertions
SourceKeyLast seenRaw
ScienceDB10.57760/sciencedb.2021311 d agoJSON v1
FieldAssertionExtractorEvidence
access_levelsource · scidb cnconnector:scidb_cn@1.0.0
concepts[field].local:field:earth-environmentalmapping · scidb cnconnector:scidb_cn@1.0.0
concepts[field].local:field:engineeringmapping · scidb cnconnector:scidb_cn@1.0.0
concepts[field].local:field:humanitiesmapping · scidb cnconnector:scidb_cn@1.0.0
concepts[field].local:field:life-sciencesmapping · scidb cnconnector:scidb_cn@1.0.0
concepts[field].local:field:social-sciencemapping · scidb cnconnector:scidb_cn@1.0.0
descriptionsource · scidb cnconnector:scidb_cn@1.0.0/metadata/dc/description
licensesource · scidb cnconnector:scidb_cn@1.0.0/metadata/dc/rights
publication_datesource · scidb cnconnector:scidb_cn@1.0.0
titlesource · scidb cnconnector:scidb_cn@1.0.0/metadata/dc/title