Abstract
Making use of microsoft visual studio, net platform, the assistant decision-making system of tunnel boring machine in tunnelling has been built to predict the time and cost. Computation methods of the performance parameters have been discussed. New time and cost prediction models have been depicted. The multivariate linear regression has been used to make the parameters more precise, which are the key factor to affect the prediction near to the reality.
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Foundation item: Supported by the Project of National Key Technology and Equipment (ZZ02-03-03-03-07)
Biography: WU Shijing (1963-), male, Professor, research direction: equipments management engineering, state monitoring and malfunction diagnostics of machine and electronic equipments.
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Shijing, W., Bo, Q. & Zhibo, G. The time and cost prediction of tunnel boring machine in tunnelling. Wuhan Univ. J. Nat. Sci. 11, 385–388 (2006). https://doi.org/10.1007/BF02832128
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DOI: https://doi.org/10.1007/BF02832128
Key words
- tunnel boring machine
- time prediction
- cost prediction
- assistant decision-making
- multivariate linear regression