| Summary: | 碩士 === 國立臺灣大學 === 土木工程學研究所 === 97 === Dynamically dimensioned search algorithm is a new type of heuristic algorithm which was originally developed by Bryan A. Tolson in 2007.
In this study, the dynamically dimensioned search algorithm is applied to automate the calibration process of a unsteady river flow model（Wu et al., 2007）in the Tamshui river basin. The observed data of Krosa（2007）typhoon flood levels are used for calibrating the resistance coefficients. Different flood events, Wipha（2007）and Mitag（2007）typhoons , are used to verify the applicability of calibrated resistance coefficients. In the studied area, the whole river systems are divided into 20 reaches, and each reach has two resistance coefficients（n_d and n_u）to be determined.
Automatic calibration proposed in the past (Chan, 2004；Huang, 2006) are based on genetic algorithms which has potentials of solving high-dimension space with good search capabilities. Since the feasible solution region in the unsteady river flow model (CCCMMOC) is too large（41^16×61^24~10^68），the complex calculus process of the genetic algorithm becomes inefficient. As a result, the dynamically dimensioned search algorithm is proposed to calibrate automatically an optimal solution set in a reasonable period of time.
The results showed that the dynamically dimensioned search algorithm is not only improving on the efficiency but also increasing the stability of calibrated results. Therefore, the dynamically dimensioned search algorithm is indeed a diverse and robust method for automatic calibration of the unsteady river flow model, CCCMMOC.
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