Exchange Place Station Subsurface Reconstruction and Improvements

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.Cost and duration, reconstruction project, regression analysis, neural networks,

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Exchange Place Station Subsurface Reconstruction and Improvements

Cited by 3 publications

References 1 publication

Predicting Cost Deviation in Reconstruction Projects: Artificial Neural Networks versus Regression

Predicting Cost Deviation in Reconstruction Projects: Artificial Neural Networks versus Regression

Reconstruction of the Building Infrastructure: Two Performance Prediction Models

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

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