A graph mining-based methodology for discovering and visualizing high-level knowledge for building energy management

Author:

Fan Cheng,Xiao FuORCID,Song Mengjie,Wang Jiayuan

Funder

Research Grant Council of the Hong Kong SAR

Natural Science Foundation of Guangdong Province, China

Philosophical and Social Science Program of Guangdong Province, China

the National Taipei University of Technology-Shenzhen University Joint Research Program

Publisher

Elsevier BV

Subject

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

Reference53 articles.

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2. Waide P, Ure J, Karagianni N, Smith G, Bordass B. The scope for energy and CO2 savings in the EU through the use of building automation technology. Final Report for the European Copper Institute. August 10, 2013.

3. A review of data-driven building energy consumption prediction studies;Amasyali;Renew Sustain Energy Rev,2018

4. Assessment of deep recurrent neural network-based strategies for short-term building energy predictions;Fan;Appl Energy,2019

5. A short-term building cooling load prediction method using deep learning algorithms;Fan;Appl Energy,2017

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