From cognitive bias toward advanced computational intelligence for smart infrastructure monitoring

Document Type

Article

Publication Date

3-1-2022

Abstract

Visual inspections have been typically used in condition assessment of infrastructure. However, they are based on human judgment and their interpretation of data can differ from acquired results. In psychology, this difference is called cognitive bias which directly affects Structural Health Monitoring (SHM)-based decision making. Besides, the confusion between condition state and safety of a bridge is another example of cognitive bias in bridge monitoring. Therefore, integrated computer-based approaches as powerful tools can be significantly applied in SHM systems. This paper explores the relationship between the use of advanced computational intelligence and the development of SHM solutions through conducting an infrastructure monitoring methodology. Artificial Intelligence (AI)-based algorithms, i.e., Artificial Neural Network (ANN), hybrid ANN-based Imperial Competitive Algorithm, and hybrid ANN-based Genetic Algorithm, are developed for damage assessment using a lab-scale composite bridge deck structure. Based on the comparison of the results, the employed evolutionary algorithms could improve the prediction error of the pre-developed network by enhancing the learning procedure of the ANN.

Keywords

Cognitive bias, Infrastructure health monitoring, Bridge monitoring, Artificial intelligence, Safety

Publication Title

Frontiers in Psychology

Divisions

biomedengine,sch_civ,mechanical

Funders

Universiti Malaya (IIRG007A-2019),Universiti Malaya (IIRG007B-2019)

Volume

13

Publisher

Frontiers Media

Publisher Location

AVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE, CH-1015, SWITZERLAND

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