CAJ | 학술논문

水文模型参数优选是水文模型研究中的重点和难点，应用传统的基于梯度下降、导数理论的优化算法难以取得较好效果。遗传算法是一种多参数、多个体全局智能优化算法，在参数优选中应用广泛且效果较好。将遗传算法应用于水箱年径流模型参数优化中，通过实例应用表明，遗传算法较传统优化算法在模型参数优选中收敛速度、成果精度等方面有所提升，效果较好。
수문모형삼수우선시수문모형연구중적중점화난점，응용전통적기우제도하강、도수이론적우화산법난이취득교호효과。유전산법시일충다삼수、다개체전국지능우화산법，재삼수우선중응용엄범차효과교호。장유전산법응용우수상년경류모형삼수우화중，통과실례응용표명，유전산법교전통우화산법재모형삼수우선중수렴속도、성과정도등방면유소제승，효과교호。
Parameter optimization of hydrolofical model is the key point and difficulty in hydrolofical model research. Traditional optimization alfo-rithms based on fradient descent and derivative theory are not effective in parameter optimization of hydrolofical model. The fenetic alforithm is a flobal optimization alforithm and widely applied in mutiparameter optimization of hydrolofical model. This paper applied the fenetic alforithm in parameter optimization of tank model. The results indicate that the fenetic alforithm achieves better effects on converfent speed and accuracy in pa-rameter optimization than traditional optimization alforithms.