Automatic building design with genetic algorithms and artificial neural networks (WIP)

Authors:
Negin Behboudi;Fouad Butt;Abdolreza Abhari
Affiliations:
Ryerson University, Toronto, Ontario, Canada;Ryerson University, Toronto, Ontario, Canada;Ryerson University, Toronto, Ontario, Canada
Venue:
Proceedings of the 2012 Symposium on Simulation for Architecture and Urban Design
Year:
2012

Citing 2
Cited 1

Automated layout design of beam-slab floors using a genetic algorithm

Computers and Structures
A soft computing method for detecting lifetime building thermal insulation failures

Integrated Computer-Aided Engineering

Data mining using ANN for finding the effects of building structure on thermal comfort parameters (WIP)

Proceedings of the Symposium on Simulation for Architecture & Urban Design

Quantified Score

Hi-index	0.00

Visualization

Abstract

It is our goal to develop an automatic system that employs soft computing techniques to automate the design process of a building. Neural networks replace simulation processes. Structural characteristics, occupant behavior and also external factors influence the thermal comfort level perceived by the occupants of a building. Conflicting design objectives of thermal comfort, structural properties and cost form a complex search space of design solutions highlighting the utility of multi-objective genetic algorithms as an attractive technique for searching the solution space.