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白洋淀天然入淀水量在长期的时间序列上有着丰、枯水期交替演化的规律,灰色波形模型适用于这一规律发展趋势的研究。通过遗传算法(GA)对灰色一阶模型(GM(1,1))的迭代基值A与背景值系数B进行优化,利用遗传算法收敛效率高,选择范围广的优点,建立了以GA2GM(1,1)群为基础的GA2灰色波形模型,对白洋淀天然入淀水量趋势进行研究。最终得出结论:GA2灰色波形模型不仅在信息序列的拟合上明显优于传统灰色波形模型,且GA2灰色波形模型能更好的抓住信息序列发展特点,更为准确的预测白洋淀天然入淀水量演化规律。说明用GA2灰色波形模型进行白洋淀天然入淀水量研究是可行的,也为研究湖泊水资源量变化提供了一种新思路。
The natural precipitation of Baiyangdian Lake has the regular evolution of abundance and dry season on the long-term time series. The gray waveform model is suitable for the study of this regular trend of development. The genetic algorithm (GA) is used to optimize the iterative basis value A and the background value coefficient B of the gray first-order model (GM (1,1)). By using the advantages of high convergence efficiency and wide range of selection, 1,1) group based GA2 gray waveform model, Baiyangdian natural precipitation water trends. Finally, the conclusion is drawn that the GA2 gray waveform model is not only better than the traditional gray waveform model in fitting the information sequence, but also the GA2 gray waveform model can better grasp the development characteristics of the information sequence and predict the natural precipitation of Baiyangdian Lake more accurately Water evolution. It is feasible to study the natural precipitation of Baiyangdian Lake by using GA2 gray waveform model, and also provide a new idea for studying the change of lake water resources.