摘要
分析了测压管水位的滞后原因,基于GA-RBF的遗传算法理念,依据库水位与测压管水位在扣除滞后时间条件下基本满足线性关系原理,对滞后时间进行了优化计算,其中对库水位和测压管水位的拟合采用径向基函数神经网络来实现。实例证明,该方法简单合理,计算精度高,其效果是令人满意的。
The paper analyzes the cause of hysteresis of piezometic tube, and based on the method of GA, hysteresis time is calculated according to reservior level is in rectilinear correlation with piezometric tube level, in which RBF is used to fit reservior level and piezometric tube level. Example shows the result is satisfactory with its high precision.
出处
《水科学与工程技术》
2005年第3期3-7,共5页
Water Sciences and Engineering Technology
基金
河北省自然科学基金资助项目(501175)
关键词
土石坝
测压管水位
滞后时间
遗传算法
神经网络
earth-rock dam
piezometric tube level
hysteresis time
genetic algorithm
radial basis function neural network
