the analysis of geochemical data in frequency domain, as indicated in this research study, can provide new exploratory informationthat may not be exposed in spatial domain. to identify deep geochemical anomalies, sulfide zone and geochemical noises in dalli cu–au porphyry deposit, a new approach based on coupling fourier transform (ft) and principal component analysis (pca) has beenused. the re...

multivariate statistical techniques such as cluster analysis, multidimensional scaling and principal component analysis were applied to evaluate the temporal and spatial variations in water quality data set generated for two years (2008-2010) from six monitoring stations of veli-akkulam lake and compared with a regional reference lake vellayani of south india. seasonal variations of 14 differen...

this paper compares clusters of aligned persian and english texts obtained from k-means method. text clustering has many applications in various fields of natural language processing. so far, much english documents clustering research has been accomplished. now this question arises, are the results of them extendable to other languages? since the goal of document clustering is grouping of docum...

in this article the methodology proposed by li and wang for mixed qualitative and quantitative modeling and simulation of temporal behavior of processing unit is reexamined and extended to more complex case. the main issue of their approach considers the multivariate statistics of principal component analysis (pca), along with clustered fuzzy digraphs and reasoning. the pca and fuzzy clustering...

this study aims to assess the effect of grazing intensity on vegetation structure, soil nutrient concentrations and soil physical properties. the study was carried out in steppe rangelands of saveh, markazi province, iran. four sites with four grazing intensities including very high, high, moderate and non-grazed with the same ecological conditions were selected. to study various vegetation and...