Machine learning approaches for predicting household transportation energy use

Machine learning approaches for predicting household transportation energy use

This paper presents four modeling techniques for predicting household transportation energy consumption by exploring decision trees, random forest, and neural networks in addition to elastic net regularization analyses. The main objective of this study is to evaluate how effectively these advanced s...

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Bibliographic Details
Main Authors: Shideh Shams Amiri, Nariman Mostafavi, Earl Rusty Lee, Simi Hoque
Format: Article
Language:English
Published: Elsevier 2020-08-01
Series:City and Environment Interactions
Subjects:
Transportation energy modeling
Household travel survey data
Machine learning
Random forest
Artificial neural network
Online Access:http://www.sciencedirect.com/science/article/pii/S2590252020300258

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http://www.sciencedirect.com/science/article/pii/S2590252020300258

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