Artificial Neural Network–Based Generative Design Optimization of the Energy Performance of Florida Single-Family Houses-Reference-Cited by-同舟云学术

Artificial Neural Network–Based Generative Design Optimization of the Energy Performance of Florida Single-Family Houses

Published:2024-03 Issue:2 Volume:38 Page:
ISSN:0887-3801
Container-title:Journal of Computing in Civil Engineering
language:en
Short-container-title:J. Comput. Civ. Eng.

Author:

Elias Rita¹,Issa Raja R. A.²^ORCID

Affiliation:

1. Ph.D. Candidate, Rinker School of Construction Management, Univ. of Florida, P.O. Box 115701, Gainesville, FL 32611-5701 (corresponding author).

2. Univ. of Florida (UF) Distinguished Professor and Director, Center for Advanced Construction Information Modeling, Rinker School of Construction Management, Univ. of Florida, P.O. Box 115701, Gainesville, FL 32611-5701. ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Link

https://ascelibrary.org/doi/pdf/10.1061/JCCEE5.CPENG-5579

Reference43 articles.

1. Optimization of envelope design for housing in hot climates using a genetic algorithm (GA) computational approach

2. Criteria-based ranking of green building design factors according to leading rating systems

3. Artificial neural networks to predict energy performance and retrofit scenarios for any member of a building category: A novel approach

4. Autodesk. 2021. “Generation settings.” Accessed March 8 2023. https://knowledge.autodesk.com/support/revit/learn-explore/caas/CloudHelp/cloudhelp/2021/ENU/Revit-Model/files/GUID-710D71BE-3376-4647-822A-DA4D793DCBFA-htm.html#:∼:text=A%20sufficient%20size%20depends%20on times%20the%20number%20of%20inputs.

5. Generation of energy-efficient architecture solutions applying GENE_ARCH: An evolution-based generative design system

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