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About An Artificial Neural Network Approach To Structural Cost Estimation
This document presents research on developing an artificial neural network (ANN) model to predict the total structural cost of building projects in the Philippines. The researchers collected data from 30 building projects and divided it into training, validation, and test sets. Six input parameters were used in the ANN: number of storeys, number of basements, floor area, volume of concrete, area of formworks, and weight of reinforcing steel. The best ANN architecture consisted of these six inputs, seven nodes in the hidden layer, and one output of total structural cost. The ANN model reasonably predicted costs with favorable training and testing results.
Detailed Information
| Author: | ['Jinhan Kim'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 8 |
| Language: | English |
| Format: | |
| Price: | FREE |
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