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首页> 外文期刊>Journal of Environmental Sciences >Projection pursuit cluster model and its application in water quality assessment
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Projection pursuit cluster model and its application in water quality assessment

机译:投影寻踪聚类模型及其在水质评价中的应用

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摘要

One of the difficulties frequently encountered in water quality assessment is that there are many factors and they cannot be assessed according to one factor, all the effect factors associated with water quality must be used. In order to overcome this issues the projection pursuit principle is introduced into water quality assessment, and projection pursuit cluster(PPC) model is developed in this study. The PPC model makes the transition from high dimension to one-dimension. In other words, based on the PPC model, multifactor problem can be converted to one factor problem. The application of PPC model can be divided into four parts: (1) to estimate projection index function Q(a); (2) to find the right projection direction 3; (3) to calculate projection characteristic value of the i th sample z_i, and (4) to draw comprehensive analysis on the basis of z_i. On the other hand, the empirical formula of cutoff radius R is developed, which is benefit for the model to be used in practice. Finally, a case study of water quality assessment is proposed in this paper. The results showed that the PPC model is reasonable, and it is more objective and less subjective in water quality assessment. It is a new method for multivariate problem comprehensive analysis.
机译:水质评估中经常遇到的困难之一是有很多因素,无法根据一种因素进行评估,必须使用与水质相关的所有影响因素。为了克服这一问题,将投影寻踪原理引入水质评价中,并建立了投影寻踪类(PPC)模型。 PPC模型实现了从高维到一维的过渡。换句话说,基于PPC模型,多因素问题可以转换为一个因素问题。 PPC模型的应用可分为四个部分:(1)估计投影指标函数Q(a); (2)找到正确的投影方向3; (3)计算第i个样本z_i的投影特征值,(4)在z_i的基础上进行综合分析。另一方面,提出了截断半径R的经验公式,对于实际使用的模型是有利的。最后,本文以水质评估为例。结果表明,PPC模型是合理的,在水质评价中较为客观,主观性较低。这是一种用于多变量问题综合分析的新方法。

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