NEUROFLOOR: A Flooring System Selection Neural Network

by Raja R. A. Issa, Univ of Florida, Gainesville, United States,
Desmond Fletcher, Univ of Florida, Gainesville, United States,



Document Type: Proceeding Paper

Part of: Computing in Civil and Building Engineering

Abstract: A back-propagation neural network (BPNN) has been trained to help building designers and engineers in designing or analyzing steel bar joist flooring systems. The NEUROFLOOR BPNN allows design professionals to speed up the design process by enabling them to start off with a reasonable steel bar joist trail size. Similarly, reasonable floor trail loads for analyzing an existing structure can be determined.

Subject Headings: Bars (structure) | Neural networks | Floors | Building design | Joists | Computer software | Network analysis

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