Department of Civil Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
Abstract
The current management system for concrete road bridges in Iran is primarily based on a descriptive model, which assesses the condition of bridge elements and assigns grades based on the level of deterioration. However, there have been concerns raised about the use of descriptive statistics when analyzing large amounts of data. In order to address these concerns, this research incorporates the data mining method known as decision tree analysis.
The decision tree analysis involves in-depth examination of data, including objective observations by experts and calculations of damage indices. Paul has introduced this method to replace descriptive analysis in his research. To conduct this study, various data such as physical characteristics, atmospheric and climatic conditions, traffic conditions, and deterioration indices (derived from established formulas and tables) of concrete bridges with spans exceeding 6 meters on a main 5-axis road in Zanjan province were collected. The decision tree method, along with Rapid Miner software, was utilized to model and analyze this data.
The research findings indicate that the decision tree method demonstrates a high level of accuracy in predicting and prioritizing factors that contribute to bridge damage, surpassing the capabilities of conventional models. Specifically, the study reveals that the percentage of heavy vehicles passing over a bridge is the most significant factor influencing its damage. Furthermore, it predicts that bridges with a percentage exceeding 19.5% would fall into the category of heavily damaged bridges.
medghalchi, A., rashvand, P., & Delnavaz, A. (2023). Prediction of Bridge Damage Factors Using Decision Tree Technique
(Case Study: Concrete Rad Bridges in ZANJAN Province-IRAN). Asas Journal, 24(69), -.
MLA
ali medghalchi; pooria rashvand; Ali Delnavaz. "Prediction of Bridge Damage Factors Using Decision Tree Technique
(Case Study: Concrete Rad Bridges in ZANJAN Province-IRAN)". Asas Journal, 24, 69, 2023, -.
HARVARD
medghalchi, A., rashvand, P., Delnavaz, A. (2023). 'Prediction of Bridge Damage Factors Using Decision Tree Technique
(Case Study: Concrete Rad Bridges in ZANJAN Province-IRAN)', Asas Journal, 24(69), pp. -.
VANCOUVER
medghalchi, A., rashvand, P., Delnavaz, A. Prediction of Bridge Damage Factors Using Decision Tree Technique
(Case Study: Concrete Rad Bridges in ZANJAN Province-IRAN). Asas Journal, 2023; 24(69): -.
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