With the view of effectively fitting the complicated water level process of the lower Yellow River, polynomial regression, stepwise regression, parameters by ridge estimate and so on, are logically integrated. And the...With the view of effectively fitting the complicated water level process of the lower Yellow River, polynomial regression, stepwise regression, parameters by ridge estimate and so on, are logically integrated. And the progressive transformation is introduced. Then a new method is put forward. The core difference of this new method from the same kind of methods lies in that in this method the strong coupling effect of weak influencing factors which is common in a complicated water level process is considered, that many effective methods are synthetically used to reduce the fitting model error, and that the necessary progressive transformation is introduced. The advantages of many theories and methods are logically integrated in this method, and the method can be easily used. The rationality and necessity of each step in this method are ensured by sufficient theories, so this method can be widely used to effectively simulate the inherent relations in the same kind of complicated data. Furthermore, many complicated water level processes of the lower Yellow River are fitted by this method, and all the fitting precisions are markedly higher than the precision by the other existing methods. Every component term in the fitting model has clear physical meaning.展开更多
基金Supported by Natural Science Fund of Hohai University (Grant No. 2007428611)
文摘With the view of effectively fitting the complicated water level process of the lower Yellow River, polynomial regression, stepwise regression, parameters by ridge estimate and so on, are logically integrated. And the progressive transformation is introduced. Then a new method is put forward. The core difference of this new method from the same kind of methods lies in that in this method the strong coupling effect of weak influencing factors which is common in a complicated water level process is considered, that many effective methods are synthetically used to reduce the fitting model error, and that the necessary progressive transformation is introduced. The advantages of many theories and methods are logically integrated in this method, and the method can be easily used. The rationality and necessity of each step in this method are ensured by sufficient theories, so this method can be widely used to effectively simulate the inherent relations in the same kind of complicated data. Furthermore, many complicated water level processes of the lower Yellow River are fitted by this method, and all the fitting precisions are markedly higher than the precision by the other existing methods. Every component term in the fitting model has clear physical meaning.
