Loads On Shores And Slabs During Multistory Structure Construction: An Artificial Neural Network Approach
Author(s) -
André Mund,
Mohammed E. Haque
Publication year - 2020
Language(s) - English
Resource type - Conference proceedings
DOI - 10.18260/1-2--10942
Subject(s) - artificial neural network , artificial intelligence , computer science , field (mathematics) , engineering , deflection (physics) , structural engineering , mathematics , physics , pure mathematics , optics
Neural computing is a relatively new field of artificial intelligence (AI), which tries to mimic the structure and operation of biological neural systems, such as the human brain, by creating an Artificial Neural Network (ANN) on a computer. Artificial Neural Networks have the ability to be trained by example. Patterns in a series of input and output values of example cases are recognized. This acquired “knowledge” can then be used by the Artificial Neural Network to predict unknown output values for a given set of input values. This paper demonstrates the feasibility of using an Artificial Neural Network (ANN) back-propagation multi-layered model to estimate loads on shores and slabs during the construction phases of a multistory structure. It also determines the number of stories above the slab with the maximum load. This model permits, in an early planning stage, to establish the minimum cycle time for the erection of stories given the number of shores and reshores to be used.
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