Multivariate relationships between campus design parameters and energy performance using reinforcement learning and parametric modeling

Author:

Chang Soowon,Saha Nirvik,Castro-Lacouture Daniel,Yang Perry Pei-Ju

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Mechanical Engineering,General Energy,Building and Construction

Reference37 articles.

1. UN. World’s population increasingly urban with more than half living in urban areas | UN DESA | United Nations Department of Economic and Social Affairs. United Nations 2014. [accessed December 5, 2018].

2. UNEP-DTIE Sustainable Consumption and Production Branch. Cities and Buildings; 2013.

3. U.S. EIA. Annual Energy Outlook 2018. US Energy Inf Adm; 2018. [accessed June 15, 2018].

4. Pérez-Lombard L, Ortiz J, Pout C. A review on buildings energy consumption information n.d. https://doi.org/10.1016/j.enbuild.2007.03.007.

5. Data-driven Urban Energy Simulation (DUE-S): a framework for integrating engineering simulation and machine learning methods in a multi-scale urban energy modeling workflow;Nutkiewicz;Appl Energy,2018

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