粒子群优化算法在马蹄形断面隧道临界深度计算中的应用

Ayoub Bahmanikashkooli , Majid Zare , Bahman Safarpour , Mostafa Safarpour
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引用次数: 7

摘要

临界水深是明渠设计、运维及渐变水流分析中的一个重要参数。对于马蹄形截面通道,控制方程在临界流深处是高度非线性的,求解隐式方程需要耗费大量时间。在目前的研究中,我们通过将临界深度方程转化为目标函数,然后利用粒子群优化算法将其最小化,计算出马蹄形通道的临界深度。通过与已有方程的比较,对模型的精度进行了评价。此外,该方法还可用于水利工程中的其他优化问题。
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Application of Particle Swarm Optimization Algorithm for Computing Critical Depth of Horseshoe Cross Section Tunnel

Critical depth is an important parameter in the design, operation and maintenance of open channels and analysis of gradually varied flow. For horseshoe cross section channels, the governing equations are highly nonlinear in the critical flow depth and thus solution of the implicit equations involves time consuming numerical methods. In current research, through conversion of critical depth equation to an objective function and then its minimization by using Particle Swarm Optimization algorithm, we calculate critical depth in horseshoe channels. The accuracy of the proposed model was also evaluated by comparing with existing equations. Furthermore this method can be used to deal with other optimization problems in hydraulic engineering.

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Contents Preface Contents Contents Lactic Acid Production from Repeated-Batch and Simultaneous Saccharification and Fermentation of Cassava Starch Wastewater by Amylolytic Lactobacillus Plantarum MSUL 702
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