Short-term prediction of building energy consumption employing an improved extreme gradient boosting model: A case study of an intake tower-Reference-Cited by-同舟云学术

Short-term prediction of building energy consumption employing an improved extreme gradient boosting model: A case study of an intake tower

Published:2020-07 Issue: Volume:203 Page:117756
ISSN:0360-5442
Container-title:Energy
language:en
Short-container-title:Energy

Author:

Lu Hongfang,Cheng Feifei,Ma Xin,Hu Gang

Funder

National Natural Science Foundation of China

State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation

Southwest Petroleum University

Humanities and Social Science Fund of Ministry of Education of China

China Scholarship Council

Publisher

Elsevier BV

Subject

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

Reference43 articles.

1. Impact of climate change on building energy use in different climate zones and mitigation and adaptation implications;Wan;Appl Energy,2012

2. Innovating to zero the building sector in europe: minimising the energy consumption, eradication of the energy poverty and mitigating the local climate change;Santamouris;Sol Energy,2016

3. A cross-country comparison of the building energy consumptions and their trends;Berardi;Resour Conserv Recycl,2017

4. Us natural gas consumption prediction using an improved kernel-based nonlinear extension of the arps decline model;Lu;Energy,2020

5. International energy outlook,2019

Cited by 79 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Forecasting operation of a chiller plant facility using data-driven models;International Journal of Refrigeration;2024-11

2. Probabilistic quantile multiple fourier feature network for lake temperature forecasting: incorporating pinball loss for uncertainty estimation;Earth Science Informatics;2024-08-17

3. Training data selection using information entropy: Application to heating load modeling of rural residence in northern China;Applied Geophysics;2024-07-10

4. Comprehensive transferability assessment of short-term cross-building-energy prediction using deep adversarial network transfer learning;Energy;2024-07

5. A novel attention-based long short term memory and fully connected neutral network approach for production energy consumption prediction under complex working conditions;Engineering Applications of Artificial Intelligence;2024-07