Prediction of residential district heating load based on machine learning: A case study-Reference-Cited by-同舟云学术

Prediction of residential district heating load based on machine learning: A case study

Published:2021-09 Issue: Volume:231 Page:120950
ISSN:0360-5442
Container-title:Energy
language:en
Short-container-title:Energy

Author:

Wei Ziqing,Zhang Tingwei,Yue Bao,Ding Yunxiao,Xiao Ran,Wang Ruzhu,Zhai Xiaoqiang

Publisher

Elsevier BV

Subject

General Energy,Pollution,Mechanical Engineering,Building and Construction,Electrical and Electronic Engineering,Industrial and Manufacturing Engineering,Civil and Structural Engineering

Reference40 articles.

1. Handbook of energy systems in green buildings;Wang;Handb Energy Syst Green Build,2018

2. Heating and cooling performance of a minitype ground source heat pump system;Zhai;Appl Therm Eng,2017

3. Investigation of annual energy performance of a VWV air source heat pump system;Wang;Int J Refrig,2018

4. Modeling and forecasting building energy consumption: a review of data-driven techniques;Bourdeau;Sustain Cities Soc,2019

5. EnergyPlus: creating a new-generation building energy simulation program;Crawley;Energy Build,2001

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