嫩江水体溶解氧变化规律的混沌研究

针对目前溶解氧研究主要是从生物、化学等方面开展,而对溶解氧自身变化规律的研究很少的特点,以嫩江干流浏园水文站测得的溶解氧质量浓度序列为例,首先进行相空间重构,应用自相关函数法确定出延迟时间、伪邻近点法确定出嵌入维数;然后应用主分量分析(PCA)方法对序列进行分析,表明该序列不是噪声序列而可能是混沌序列,通过计算Kolmogorov熵得出溶解氧质量浓度序列具有混沌特性的结论;最后应用基于关联度的局域加权线性回归预测法对该序列进行了混沌预测研究,得到了比较理想的预测结果,这为应用混沌理论进行溶解氧变化规律的研究提供了依据.

Chaos analysis of the changing regularity of the dissolved oxygen of Nenjiang-River water body

The present water is aimed at introducing our study of the dissolved oxygen concentration series, which helps to detect the changing regularity of the main stream of Nenjiang River at Liuyuan Hydrology Station along the river. As is known, dissolved oxygen is a principal index indicating the river water quality and its evolution situation, whose change may directly influence our water environment. For this purpose, the authors of this paper have done a lot of contrast experiments with the river water change tough biological and chemical means in order to find the changing regularity of the dissolved oxygen in the river water itself. In doing so, we have worked out the delaying time of the series by the automatic correlation function and the embedding dimension of the series with the false neighbor metbod. Then, we have calculated the results by using the method of principal component analysis and found the dissolved oxygen concentration series, which shows that the data series is not of noise in nature, rather likely to be chaos. The final conclusion is made by calculating the kolmogorov entropy based on the reconstruction of state space, verifying file chaotic nature of the dissolved oxygen concentration. In addition, we have tried to apply the method of local addingweight linear regression to forecast-making based on the degree of incidence to the series and the ideal results obtained. Thus, it has been made realistic to use the theoretical evidence to the study of the changing regularity of the dissolved oxygen.