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280.188  Articles
1 of 28.020 pages  |  10  records  |  more records»
This paper aims to explore spatial heterogeneity present in the crop yields data collected from 170 administrative districts in the forest and forest-steppe zones of Ukraine for 27 years using the PCA and GWPCA methods. As a result of the principal compon... see more

Face recognition is one of many important researches, and today, many applications have implemented it. Through development of techniques like Principal Components Analysis (PCA), computers can now outperform human in many face recognition tasks, particul... see more

Factor analysis (principal components analysis is a factor method) of downsizing thecomplexity of data and fixing the number of principal components to be retained in the final model. Inthis paper we present the usefulness of Principal Components Analysis... see more

Groundwater drinking water supply surveillance data were accessed to summarize water quality delivered as public and private water supplies in southern Saskatchewan as part of an exposure assessment for epidemiologic analyses of associations between water... see more

This paper presents a way of predicting the biochemical oxygen demand (BOD) of the output stream of the activated sludge of a food processing industry. A combination of principal components analysis (PCA) and artificial neural networks (ANN) was used to d... see more

In the present article, the patterns of the geographic variability in yields of rye within Polesia and the Forest-Steppe zone of Ukraine are presented and the correlation of the factors and dynamics of an agroeconomic and agroecological nature was determi... see more

Cheese yield is affected by many factors including milk quality and composition. The application of a factor analysis method, so called Principal Components Analysis (PCA), has the final goal of establishing and analyzing those variables which influence i... see more

Principal Component Analysis is a method factor - factor analysis - and is used to reduce data complexity by replacingmassive data sets by smaller sets. It is also used to highlight the way in which the variables are correlated with eachother and to deter... see more

Principal Components and Classification Analysis (PC&CA) represents one of the most utilised multivariate chemometric techniques, having the advantage to use many measurements for a single sample in the same time, being recommended for understanding bette... see more

1 of 28.020 pages  |  10  records  |  more records»