Multi-objective optimization of building energy performance and indoor thermal comfort by combining artificial neural networks and metaheuristic algorithms-Reference-Cited by-同舟云学术

Multi-objective optimization of building energy performance and indoor thermal comfort by combining artificial neural networks and metaheuristic algorithms

Published:2021-05 Issue: Volume:239 Page:110839
ISSN:0378-7788
Container-title:Energy and Buildings
language:en
Short-container-title:Energy and Buildings

Author:

Chegari Badr,Tabaa Mohamed,Simeu Emmanuel,Moutaouakkil Fouad,Medromi Hicham

Funder

CNRST

Publisher

Elsevier BV

Subject

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

Reference73 articles.

1. Ministère de l’Energie des Mines de l’Eau et de l’Environnement, Stratégie Energétique Nationale – Horizon 2030, 2015.

2. Buildings – Energy Efficiency – Department of Housing and Urban Policy [Online], Available: http://www.mhpv.gov.ma/?page_id=3605, (Accessed: 01-Jan-2021).

3. AMEE, Règlement thermique de construction au Maroc (RTCM), vol. 91, 2014.

4. Algorithms for optimization of building design: a review;Machairas;Renew. Sustain. Energy Rev.,2014

5. An efficient metamodel-based method to carry out multi-objective building performance optimizations;Bre;Energy Build.,2020

Cited by 110 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. A novel multi-objective generative design approach for sustainable building using multi-task learning (ANN) integration;Applied Energy;2024-12

2. Dynamic energy optimization strategy to provide appropriate thermal comfort and fresh air under occupants’ different activity types;Energy and Buildings;2024-10

3. Building Information Modeling and AI Algorithms for Optimizing Energy Performance in Hot Climates: A Comparative Study of Riyadh and Dubai;Buildings;2024-09-02

4. Multi-objective optimization of rural residential envelopes in cold regions of China based on performance and economic efficiency;Case Studies in Thermal Engineering;2024-09

5. Energy retrofitting of hospital buildings considering climate change: An approach integrating automated machine learning with NSGA-III for multi-objective optimization;Energy and Buildings;2024-09