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Your search keyword '"Cheng, Ying-Mei"' showing total 15 results
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15 results on '"Cheng, Ying-Mei"'

2. A Framework for Semantic Interoperability in 3D Tangible Cultural Heritage in Taiwan

Author

Kuo, Chiao-Ling, Cheng, Ying-Mei, Lu, Yi-Chou, Lin, Yu-Chieh, Yang, Wun-Bin, Yen, Ya-Ning, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Pandu Rangan, C., Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Ioannides, Marinos, editor, Fink, Eleanor, editor, Brumana, Raffaella, editor, Patias, Petros, editor, Doulamis, Anastasios, editor, Martins, João, editor, and Wallace, Manolis, editor

Published
2018
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15. Short-Interval Dynamic Forecasting for Actual S-Curve in the Construction Phase.

Author

Cheng, Ying-Mei, Yu, Chih-Han, and Wang, Huai-Tien

Subjects
*CONSTRUCTION management, *COST estimates, *CONSTRUCTION cost estimates, *CONSTRUCTION costs, *CONSTRUCTION industry, *GOLDEN ratio
Abstract

Traditional approaches for cost forecasting tend to utilize a single model for the entire construction period. However, a construction project, consisting of different stages, will incur different costs, which may not be accurately captured by a single model. Gates separated the S-curve into three periods. Utilizing the same approach, the accuracy of cost forecasting can be improved by dividing the entire duration of a construction project into three periods. Therefore, this research aims at improving the traditional Grey prediction model by defining the suitable α instead of using 0.5. This new technique applies the golden section and bisection method to optimize α and build the short-interval cost-forecasting model. In each period of the construction phase, a customized optimization-forecasting model is used to estimate each short-interval cost. The proposed models should more closely predict the short-interval cost, which can be utilized to more accurately forecast the expenditure of the subsequent month within each period. [ABSTRACT FROM AUTHOR]

Published
2011
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