Title :
Hierarchic Genetic Algorithm for the Initial Omission Settlement of the Earth-Rock Dam
Author :
Song-Hui Li ; Zhi-Hong Qie ; Ji-Jian Lian ; Chun-Di Si
Author_Institution :
Tian Jin Univ., Tianjin
Abstract :
The exterior and interior displacements of the earth-rock dam are the important characters which can reflect its operation state. And it also has pivotal function in evaluating the quality of the project and judging whether the crack of the dam appears. The initial omission settlement is a popular problem in the observation of the earth-rock distortion. Because of the constructing schedule, the settlement observation dot is usually set at the time of the revetment accomplished simultaneously or after it finished. And at this time, it will be longer than the time which the dam spend reaching its elevation. Thus, a time difference existed. The quickest phase is just formed during this longer time when the settlement has grown. Usually, more than half of the total settlement has been accomplished during this time. The result shows that not only can the measure not reflect the whole process of the settlement, but the value of the measurement is far away from the fact as well, which makes the value of the observation result discounted greatly. Therefore, whether the calculation for the Initial Omission Settlement of Earth-rock Dam is right appears. The accuracy of these data has a direct influence on the reliability of the conclusion. In the paper, the initial omission settlement of earth-rock dam is optimized based on Hierarchic Genetic Algorithm by setting the omission settlement as new regression gene and optimizing the three parameters in different GA layers. The result has been testified that the value obtained from the HGA model is better than the one from early model which is far away from the real settlement process.
Keywords :
construction; dams; genetic algorithms; constructing schedule; earth-rock dam; earth-rock distortion; hierarchic genetic algorithm; initial omission settlement; settlement observation dot; Agriculture; Civil engineering; Cybernetics; Earth; Educational institutions; Equations; Genetic algorithms; Machine learning; Reservoirs; Testing; Earth-rock dam; Hierarchic Genetic Algorithm; Initial omission settlement;
Conference_Titel :
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-0972-3
DOI :
10.1109/ICMLC.2007.4370282