论文部分内容阅读
针对目前月降雨序列混沌特性研究中存在的问题,以广东省西江流域高要站月降雨序列为例,运用功率谱方法、主成分分析法、饱和关联维数法、C-C方法进行了混沌特性的判定及特征参数的求取,同时分析了数据长度和噪声对混沌研究的影响。研究结果表明,利用功率谱方法进行混沌判定时,单纯的根据连续多峰的噪声背景作为判定混沌存在的依据并不可靠;饱和关联维数法仅从能量角度对混沌序列进行判定,此外,对混沌序列进行滤波会导致此法判定结果的稳健性降低,C-C方法证明了其计算结果的可靠性;为计算出相对稳定的饱和关联维D2,计算数据的长度至少应为450个点;递归图及相应的各种定量判定标准验证了改进的双小波空域降噪方法可有效去除混沌序列中噪声的影响。
Aiming at the problems existing in the research on the chaotic characteristics of the current monthly rainfall series, taking the monthly rainfall series of Gaoyao Station in the Xijiang River valley of Guangdong Province as an example, the power spectrum method, the principal component analysis, the saturated correlation dimension method and the CC method were used to study the chaotic characteristics Judgment and characteristic parameters, and analyze the influence of data length and noise on chaos research. The results show that when the power spectrum method is used to determine the chaos, simply based on the continuous multi-peak noise background as the basis for judging the existence of chaos is not reliable. Saturated correlation dimension method only judges the chaotic sequence from the energy point of view. In addition, The chaos sequence filtering will lead to the reduction of the robustness of the results of this method, CC method to prove the reliability of the calculation results; To calculate the relatively stable saturation-related dimension D2, the length of the calculated data should be at least 450 points; And the corresponding quantitative criteria verify that the improved dual wavelet spatial denoising method can effectively remove the influence of noise in the chaotic sequence.