摘要
O’connor模型是一个比广泛应用的Streeter－Philips模型更精确的水质模型，由于该模型参数率定的困难性，限制了它在实际中的应用。通过探讨用新近发展起来的遗传算法率定该模型参数，获得了比其他方法如网格法和单纯形法更高精度的参数值，使O’connor模型的广泛应用成为可能，并为水质模型参数识别提供了一条新途径。
The genetic algorithm is a new optimization method that combines certainty with randomness in searching process so that the optimization solution of a global problem is possible to be obtained. The method is employed to identify parameters of O'Connor water quality model that is one of accurate water quality models. As result, the parameters obtained by this method are more precision than them by other optimization techniques, such as grid method and simplex search method. Therefore, the genetic algorithm is an efficient and more precision method for identification of parameters in water quality models.
出处
《环境污染与防治》
CAS
CSSCI
CSCD
北大核心
1999年第5期37-39,42,共4页
Environmental Pollution & Control
关键词
水质模型
参数识别
遗传算法
水质监测
Water quality model
Parameter identification
Genetic algorithm
