Comparison of Support Vector Machine, Gaussian Process Regression and Decision Tree Models for Energy Consumption Prediction of Campus Buildings-Reference-Cited by-同舟云学术

Comparison of Support Vector Machine, Gaussian Process Regression and Decision Tree Models for Energy Consumption Prediction of Campus Buildings

Published:2022-11-25 Issue: Volume: Page:
ISSN:
Container-title:2022 8th International Conference on Hydraulic and Civil Engineering: Deep Space Intelligent Development and Utilization Forum (ICHCE)
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Author:

Han Bo¹,Zhang Shan²,Qin Liyun¹,Wang Xianda¹,Liu Yuanyuan¹,Li Zhiyong¹

Affiliation:

1. School of Civil Engineering, North China University of Technology,Beijing,China

2. School of Information, North China University of Technology,Beijing,China

Publisher

IEEE

Link

Reference10 articles.

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2. Hourly energy consumption prediction of office buildings based on support vector machine [J/OL];xiao;Journal of Shanghai Jiao Tong University,2021

3. Analysis and Comparison of Several Classification Algorithms for Decision Tree [J];xu;Computer Knowledge and Technology,2018

4. International research and application progress of urban building energy consumption prediction model [J];leng;The Journal of Architecture,2015

5. Application of building energy consumption forecasting technology[J];wang;Shandong Industrial Technology,2017

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