Machine Learning (ML) as a surrogate model for early-stage energy optimization
Paper in proceeding, 2024

Machine learning, artificial intelligence

architecture design variables

early design

Machine learning

artificial intelligence

Author

Xinyue Wang

Chalmers, Architecture and Civil Engineering, Building Technology

Josie Harrison

Chalmers, Architecture and Civil Engineering, Building Technology

Robin Teigland

Chalmers, Technology Management and Economics, Entrepreneurship and Strategy

Alexander Hollberg

Chalmers, Architecture and Civil Engineering, Building Technology

SimBuild Conference Proceedings

0000-0000 (ISSN)

Vol. 11

IBPSA-USA SimBuild 2024 Conference
Denver, USA,

Mainstreaming holistic life cycle performance optimisation in early design stages of buildings

Swedish Energy Agency (51715-1), 2021-01-01 -- 2024-12-31.

Stakeholder-specific environmental and economic optimization of buildings in early design stages

Formas (2020-00934), 2021-01-01 -- 2024-12-31.

Subject Categories

Production Engineering, Human Work Science and Ergonomics

Energy Engineering

Computational Mathematics

Transport Systems and Logistics

Computer Science

Areas of Advance

Information and Communication Technology

More information

Latest update

6/27/2024