Research and application of rough set attribute reduction algorithm based on genetic algorithm in pipeline network
Year: 2024
Type: conference-paper
Abstract: Explosion accidents often occur in urban underground pipeline network systems, which has caused safety issues in public life and industrial production. GIS technology can visually manage pipeline equipment and solve the problem of valve closure analysis in the event of current accidents, avoiding the escalation of the situation, but it cannot make predictions. Attribute reduction is one of the core contents of rough set theory and is an NP-hard problem. This article proposes a custom attribute reduction algorithm based on an algorithm and uses the algorithm in the historical burst pipeline dataset of the water supply pipeline industry. The results have shown that this method combined with a decision tree can make predictions before water pipe leakage. The algorithm provides the best result of attribute reduction for decision tree methods, which will improve the speed and accuracy of decision-making.
Authors: Hong Li, kai Zhou, Zhao Zhuang
Institution: Guangdong University of Science and Technology
Language: English
Topic: Rough Sets and Fuzzy Logic
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4401517359