This study paper is an attempt to bring to light a new approach in the treatment of the Gaussian function. The Gaussian function is considered the basis for building the elements of the kernel matrix within the methodology of the kernel principal components that aims to reduce the dimensions and then determine the most influential variables. Besides, it works on reducing the mathematical complexity that can arise because of multidimensionality, especially if it is the data suffers from a non-linear problem in describing the relationships. This research paper has included processing the introductory parameter matrix (H) by adopting two types of matrices, namely (H ¹ diagonal, and H ² hybrid diagonal). For achieving the benefit of this paper, it has been applied to the phenomenon of salt concentrations in Shatt al-Arab water in Basra Governorate through a number of climatic variables for identification of the most influential variables. The modified Gaussian function (MGK) was used and compared with the traditional method (TGK) by adopting two methods of estimating the introductory parameter matrix H. The simulation results brought to light that the (MGK) could not achieve better results than the (TGK) for any type of matrices (H ¹ & H ²), estimated by the two methods (NS-R, ROT). Despite this fact, the (MGK) and (TGK) were consistent in determining the climatic variables most affected by the rise in salt concentrations when adopting the (NS-R) method, which are (air temperature, minimum temperature, maximum temperature, and solar brightness). While when adopting the (ROT), the (MGK) determined other variables, while the traditional method identified the same variables mentioned above.

中文翻译：

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使用改进的核主成分分析识别影响阿拉伯河水中盐浓度水平的变量

这篇研究论文试图揭示一种治疗高斯分布的新方法功能。高斯功能被认为是在核主成分方法中构建核矩阵元素的基础，旨在减少维度，然后确定最有影响力的变量。此外，它还致力于降低由于多维性而可能出现的数学复杂性，特别是当数据在描述关系时遇到非线性问题时。本研究论文包括处理介绍性参数矩阵（H）采用两种类型的矩阵，即（H ¹对角线，和H ²混合对角线）。为了实现本文的目的，通过一些气候变量将其应用于巴士拉省阿拉伯河水中的盐浓度现象，以识别最具影响力的变量。修改后的高斯功能采用两种估计引入参数矩阵H的方法，将(MGK)与传统方法(TGK)进行比较。仿真结果表明，对于任何类型，(MGK)都不能取得比(TGK)更好的结果矩阵 (H ¹ &H ²），通过两种方法（NS-R，ROT）估计。尽管如此，在采用（NS-R）方法时，（MGK）和（TGK）在确定受盐浓度上升影响最大的气候变量方面是一致的，即（气温、最低温度、最高温度和太阳亮度）。而当采用（ROT）时，（MGK）确定了其他变量，而传统方法确定了上述相同的变量。