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Peeking inside the black-box: Explainable machine learning applied to household transportation energy consumption

  • Published:2021-07 Issue: Volume:88 Page:101647
  • ISSN:0198-9715
  • Container-title:Computers, Environment and Urban Systems
  • language:en
  • Short-container-title:Computers, Environment and Urban Systems

Author:

Shams Amiri Shideh,Mottahedi Sam,Lee Earl Rusty,Hoque Simi

Funder

National Science Foundation

Publisher

Elsevier BV

Subject

Urban Studies,General Environmental Science,Ecological Modelling,Geography, Planning and Development

Reference34 articles.

1. Peeking inside the black-box: A survey on explainable artificial intelligence (XAI);Adadi;IEEE Access,2018

2. Machine learning approaches for predicting household transportation energy use;Amiri;City and Environment Interactions,2020

3. Development of transport mode choice model by using adaptive neuro-fuzzy inference system;Andrade;Transportation Research Record: Journal of the Transportation Research Board,2006

4. Interpretable models from distributed data via merging of decision trees;Andrzejak,2013

5. Multilayer feedforward networks for transportation mode choice analysis: An analysis and a comparison with random utility models;Cantarella;Transportation Research Part C: Emerging Technologies,2005

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