In this paper, a new fault identification procedure based on Kernel Principal Component Analysis (KPCA) is proposed. In contrast to the linear PCA, a key disadvantage of the KPCA is that it cannot be used directly for fault identification, e.g. using contribution plots. Therefore, a fault identification strategy based on the power series approximation of the kernel functions is proposed. To dem...

the objectives of the present study were to evaluate spring wheat recombinant inbred lines (rils) of diverse origin by estimating genetic parameters viz., variability, character association, cluster analysis, and principal component analysis (pca) for spot blotch resistance and yield components at bhu agricultural research farm during 2010-2011. grain yield per plot was significantly and positi...

In many fields of research, so-called 'multiblock' data are collected, i.e., data containing multivariate observations that are nested within higher-level research units (e.g., inhabitants of different countries). Each higher-level unit (e.g., country) then corresponds to a 'data block'. For such data, it may be interesting to investigate the extent to which the correlation structure of the var...

one priority of planning at the regional level is to recognize the system of residence and particularly its urban system. one of the features of urban system in each area or country is the way of population distribution between the cities of these areas which is called city distribution size. in functional analysis of mazandaran province 41 development indexes of educational, cultural, social, ...