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Taipei metropolitan area is a densely populated urban place. Side-by-side crowded building can be seen everywhere. Not only does rapid urban development result that old and new buildings are mixed together, but also buildings are crack or fallen down because the geological condition could not be fully predicted. Therefore, the certain risk exists on the adjacent property damage caused by construction. Construction companies are always on the disadvantaged side for the disputed events. To face the blame and claim from the public or the government, they mostly choose payout to avoid the consequence trouble. Based on this situation, construction companies need to do investigations and engineering methods assessment in advance. They should analyze the accident factors, provide the strategy and estimate the relative expense to face the claim of disputed events in order not to over the construction budget. This study collected relevant domestic literature and deliberated the Taipei metropolitan data about the adjacent property damage caused by construction. By analyzing the accidents and doing a pilot test, I figured out 14 primary factors that contain 52 secondary items. Using MATLAB software created a neural network model for designing the optimal model. Thereafter, I chose the relevant factors and used above neural network model to estimate the cost of adjacent property damage caused by foundation excavation on the bidding stage. In order to estimate the cost, each company should consider the former experiences and compensation cases of itself to adjust the factors of model.
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