Basic Multivariate Statistical Methods for Environmental Monitoring Data Mining: Introductory Course for Master Students

IF 0.7 Q3 MULTIDISCIPLINARY SCIENCES Chemistry-Didactics-Ecology-Metrology Pub Date : 2020-12-01 DOI:10.2478/cdem-2020-0002
V. Simeonov
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引用次数: 1

Abstract

Abstract The present introductory course of lectures summarizes the principles and algorithms of several widely used multivariate statistical methods: cluster analysis, principal components analysis, principal components regression, N-way principal components analysis, partial least squares regression and self-organizing maps with respect to their possible application in intelligent analysis, classification, modelling and interpretation to environmental monitoring data. The target group of possible users is master program students (environmental chemistry, analytical chemistry, environmental modelling and risk assessment etc.).
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环境监测数据挖掘的多元统计方法基础硕士导论
摘要本课程的介绍性课程总结了几种广泛使用的多元统计方法的原理和算法:聚类分析、主成分分析、主成份回归、N向主成分分析,偏最小二乘回归和自组织映射,以及它们在智能分析中的可能应用,环境监测数据的分类、建模和解释。可能用户的目标群体是硕士项目学生(环境化学、分析化学、环境建模和风险评估等)。
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来源期刊
Chemistry-Didactics-Ecology-Metrology
Chemistry-Didactics-Ecology-Metrology MULTIDISCIPLINARY SCIENCES-
CiteScore
1.50
自引率
50.00%
发文量
2
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