摘要
提出了建立双线性模型(BM)的一套简便通用的方法。用加速遗传算法可同时估计BM 模型各参数,成功地解决了BM建模这一难题,为BM模型的广泛应用提供了新工具。实例计算 结果说明:用这套方法预测地下水位动态是可行而有效的;通过利用预测过程中产生的残差信 息进行反馈矫正,保证了BM模型劫高的拟合精度和稳健的预测性能,增强了对复杂非线性动态 系统的适应性。
A simple and universal scheme is presented for establishing the bilinear time series model (BM). All parameters of the BM can be optimized at the same time with the accelerating genetic algorithm developed by the authors, and the difficulty of modeling the BM is resolved, which gives a new tool for widely applying the BM. The examples show that the scheme applied to predicting groundwater level regime is practical and efficient, and the BM can ensure high fitting precision, robust forecasting and good adaptability to complex nonlinear dynamic systems by using the feedback information of prediction residual errors. As a general method, the scheme can be applied to the forecasting of nonlinear time series in various engineering practices.
出处
《水科学进展》
EI
CAS
CSCD
北大核心
2001年第3期361-366,共6页
Advances in Water Science
基金
国家自然科学基金(49871018)
中国博士后科学基金
四川大学高速水力学国家重点实验室开放基金(9904)资助项目。
关键词
地下水位
双线性模型
遗传算法
动态预测
Error analysis
Forecasting
Genetic algorithms
Mathematical models
Nonlinear systems
Optimization
Time series analysis