Technology reports of the Yamaguchi University

Back to Top

Technology reports of the Yamaguchi University Volume 5 Issue 5
published_at 1996-12

Development of neuro-fuzzy expert system for serviceability assessment of concrete bridges

Development of neuro-fuzzy expert system for serviceability assessment of concrete bridges
Kushida Moriyoshi
fulltext
1.95 MB
KJ00004351185.pdf
Descriptions
Efforts to develop practical expert systems have been mostly concentrated on how to implement experience-based machine learning successfully. Recently several active researches on machine learning have been undertaken from the viewpoints of knowledge base management. The aim of this study is to develop the Concrete Bridge Rating (Diagnosis) Expert System with machine learning employing the combination of neural networks and bidirectional associative memories (BAM). Introduction of machine learning into this system facilitates knowledge base refinement. By applying the system to an actual in-service bridge, it has been verified that the employed machine learning method using results of questionnaire surveys on bridge experts is effective for the system.
Creator Keywords
concrete bridge
serviceability assessment
expert system
fuzzy rule
neural network
machine learning