Enhancing residential heating load prediction with advanced machine learning and optimization techniques-Reference-Cited by-同舟云学术

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Enhancing residential heating load prediction with advanced machine learning and optimization techniques

Published:2024-10 Issue: Volume:95 Page:110199
ISSN:2352-7102
Container-title:Journal of Building Engineering
language:en
Short-container-title:Journal of Building Engineering

Author:

Mohebbi Milad^ORCID,Afzal Sadegh^ORCID

Publisher

Elsevier BV

Reference40 articles.

1. A new optimized configuration for capacity and operation improvement of CCHP system based on developed owl search algorithm;Cao;Energy Rep.,2020

2. Building heating and cooling load prediction using ensemble machine learning model;Chaganti;Sensors,2022

3. Model input selection for building heating load prediction: a case study for an office building in Tianjin;Ding;Energy Build.,2018

4. Heat load prediction in district heating systems with adaptive neuro-fuzzy method;Shamshirband;Renew. Sustain. Energy Rev.,2015

5. Improving the prediction of heating energy consumed at residential buildings using a combination of support vector regression and meta-heuristic algorithms;Khajavi;Energy,2023

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