A hybrid deep learning-based method for short-term building energy load prediction combined with an interpretation process-Reference-Cited by-同舟云学术

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A hybrid deep learning-based method for short-term building energy load prediction combined with an interpretation process

Published:2020-10 Issue: Volume:225 Page:110301
ISSN:0378-7788
Container-title:Energy and Buildings
language:en
Short-container-title:Energy and Buildings

Author:

Zhang Chaobo,Li Junyang,Zhao Yang,Li Tingting,Chen Qi,Zhang Xuejun

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Mechanical Engineering,Building and Construction,Civil and Structural Engineering

Reference61 articles.

1. Management of next-generation energy using a triple bottom line approach under a supply chain framework;Ahmed;Resour. Conserv. Recycl.,2019

2. How does an industry manage the optimum cash flow within a smart production system with the carbon footprint and carbon emission under logistics framework?;Sarkar;Int. J. Prod. Econ.,2019

3. A review of data mining technologies in building energy systems: Load prediction, pattern identification, fault detection and diagnosis;Zhao;Energy Built Enviro.,2019

4. Building electric energy prediction modeling for BEMS using easily obtainable weather factors with Kriging model and data mining;Ku;Build. Simul.,2018

5. Short-term forecast model of cooling load using load component disaggregation;Lin;Appl. Therm. Eng.,2019

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