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吴光琼.群居蜘蛛优化算法在水文频率曲线参数优化中的应用水资源与水工程学报[J].,2015,26(6):123-126
群居蜘蛛优化算法在水文频率曲线参数优化中的应用
Application of social spider optimization algorithm in parameter optimization of hydrological frequency curve
  
DOI:10.11705/j.issn.1672-643X.2015.06.022
中文关键词:  群居蜘蛛优化算法  水文频率分析  优化适线法  参数优化
英文关键词:social spider optimization algorithm(SSO)  hydrological frequency analysis  optimal curve fitting method  parameter optimization
基金项目:
作者单位
吴光琼 (云南省水文水资源局 丽江分局 云南 丽江 674199) 
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中文摘要:
      利用一种新型群体智能仿生算法——群居蜘蛛优化算法(SSO)优化水文频率曲线参数,以云南省丽江仁里站和总管田站年径流量数据为例进行实例研究,分别将离差平方和准则(OLS)、离差绝对值和准则(ABS)以及相对离差平方和准则(WLS)作为SSO算法最优适应度函数对皮尔逊Ⅲ型分布参数进行优化,优化结果与粒子群优化算法(PSO)、矩法进行对比。结果表明:利用SSO算法优化仁里站和总管田站得到的OLS、ABS、WLS均优于PSO算法及矩法,比矩法提高了11%以上。SSO算法具有收敛速度快、全局寻优能力强等特点,基于SSO算法的优化适线法能够降低水文频率的分析误差,有效提高理论频率曲线与实测数据的拟合精度,是一种可行的水文频率分析方法。
英文摘要:
      The paper used a new kind of swarm intelligent bionic algorithm——communal spiders optimization (SSO) to optimize hydrologic frequency curve parameter.Taking the runoff data at Renli and Zongguantian station along Lijiang of Yunnan Province as an example for case study, the paper respectively let the square error criterion (OLS), deviation of absolute value and criterion (ABS) and relative deviation square and criterion (WLS) as SSO algorithm optimal adaptation degree function to optimize Pearson type III distribution parameters.Then it compared the optimized results with that of particle group optimization algorithm (PSO) and moment method. The results show that SSO, WLS and OLS at Renli station and Zongguan station are better than PSO algorithm and ABS algorithm, the result increased by more than 11%. SSO algorithm has fast convergence speed and strong global search optimization ability and so on .Based on that the optimal curve fitting method of SSO algorithm can decrease the analysis error of hydrological frequency and effectively improve the accuracy of theoretical frequency curves with measured data fitting ,so it is a feasible h analysis method of ydrological frequency.
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