A general multi-source ensemble transfer learning framework integrate of LSTM-DANN and similarity metric for building energy prediction-Reference-Cited by-同舟云学术

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A general multi-source ensemble transfer learning framework integrate of LSTM-DANN and similarity metric for building energy prediction

Published:2021-12 Issue: Volume:252 Page:111435
ISSN:0378-7788
Container-title:Energy and Buildings
language:en
Short-container-title:Energy and Buildings

Author:

Fang Xi,Gong Guangcai,Li Guannan,Chun Liang,Peng Pei,Li Wenqiang

Funder

Hunan Provincial Science and Technology Department

Publisher

Elsevier BV

Subject

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

Reference40 articles.

1. Is solar power renewable and carbon-neutral: evidence from a pilot solar tower plant in China under a systems view;Wu;Renewable Sustainable Energy Rev.,2021

2. Artificial intelligence-based fault detection and diagnosis methods for building energy systems: advantages, challenges and the future;Zhao;Renewable Sustainable Energy Rev.,2019

3. Modeling techniques used in building HVAC control systems: a review;Afroz;Renewable Sustainable Energy Rev.,2018

4. A review of data-driven building energy consumption prediction studies;Amasyali;Renewable Sustainable Energy Rev.,2018

5. Smart energy forecasting strategy with four machine learning models for climate-sensitive and non-climate sensitive conditions;Ahmad;Energy,2020

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