Approximately predicting the cost and duration of school reconstruction projects in Taiwan

Regression and neural network models have been developed to predict the cost and duration of projects for the reconstruction of schools which must be quickly rebuilt. Data for the school reconstruction projects in central Taiwan, which received the most serious damage from the Chi‐Chi Earthquake, were collected and analysed. The analytical results demonstrate that the floor area provides a good basis for estimating the cost and duration of school reconstruction projects, and suggest that the neural network model with back‐propagation learning technique is a feasible approach that yields better prediction results than the regression model for school reconstruction projects.

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