Open AccessMachine learning-based cost predictive model for better operating expenditure estimations of U.S. light rail transit projects
Author(s) -
Gordon Zhou,
Amir H. Etemadi,
A. A. Mardon
Publication year - 2022
Publication title -
journal of public transportation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.721
H-Index - 25
eISSN - 2375-0901
pISSN - 1077-291X
DOI - 10.1016/j.jpubtr.2022.100031
Subject(s) - operating expense , transit (satellite) , public transport , unit (ring theory) , computer science , light rail transit , operating cost , regression analysis , operations research , transport engineering , engineering , machine learning , economics , finance , mathematics education , mathematics , waste management
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