AI-Based Damage Risk Prediction Model Development Using Urban Heat Transport Pipeline Attribute Information

AI-Based Damage Risk Prediction Model Development Using Urban Heat Transport Pipeline Attribute Information

This study analyzed the probability of damage in heat transport pipelines buried in urban areas using pipeline attribute information and damage history data and developed an AI-based predictive model. A dataset was constructed by collecting spatial and attribute data of pipelines and defining basic...

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Bibliographic Details
Main Authors: Sungyeol Lee, Jaemo Kang, Jinyoung Kim, Myeongsik Kong
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Applied Sciences
Subjects:
heat transport pipelines
damage probability prediction
risk mapping
pipeline infrastructure management
machine learning
Online Access:https://www.mdpi.com/2076-3417/15/14/8003
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