High cut slopes have been widely formed due to excavation activities during the period of immigrant relocation in the reservoir area of the Three Gorges, China. Effective reinforcement meas-ures must be taken to guara...High cut slopes have been widely formed due to excavation activities during the period of immigrant relocation in the reservoir area of the Three Gorges, China. Effective reinforcement meas-ures must be taken to guarantee the stability of the slopes and the safety of residents. This article pre-sents a comprehensive method for integrating particle swarm optimization （PSO） and support vector machines （SVMs）, combined with numerical analysis, to handle the determination of appropriate rein-forcement parameters, which guarantee both slope stability and lower construction costs. The relation-ship between reinforcement parameters and slope factor of safety （FOS） and construction costs is in-vestigated by numerical analysis and SVMs, PSO is adopted to determine the best SVM performance resulting in the lowest construction costs for a given FOS. This methodology is demonstrated by a prac-tical reservoir high cut slope stabilised with anti-sliding piles, which is located at the Xingshan （兴山） County of Hubei （湖北） Province, China. The determination process of reinforcement parameters is discussed profoundly, and the pile spacing, length, and section dimension are obtained. The results pro-vide a satisfactory reinforcement design, making it possible a signficant reduction in construction costs.展开更多
基金supported by the National Natural Science Foundation of China (Nos. 40902091, 51178187)the Special Funds for Major State Basic Research Project (No. 2010CB732006)
文摘High cut slopes have been widely formed due to excavation activities during the period of immigrant relocation in the reservoir area of the Three Gorges, China. Effective reinforcement meas-ures must be taken to guarantee the stability of the slopes and the safety of residents. This article pre-sents a comprehensive method for integrating particle swarm optimization （PSO） and support vector machines （SVMs）, combined with numerical analysis, to handle the determination of appropriate rein-forcement parameters, which guarantee both slope stability and lower construction costs. The relation-ship between reinforcement parameters and slope factor of safety （FOS） and construction costs is in-vestigated by numerical analysis and SVMs, PSO is adopted to determine the best SVM performance resulting in the lowest construction costs for a given FOS. This methodology is demonstrated by a prac-tical reservoir high cut slope stabilised with anti-sliding piles, which is located at the Xingshan （兴山） County of Hubei （湖北） Province, China. The determination process of reinforcement parameters is discussed profoundly, and the pile spacing, length, and section dimension are obtained. The results pro-vide a satisfactory reinforcement design, making it possible a signficant reduction in construction costs.
