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It used a 'sequential exploratory design' (qual→Quan) mixed method approach containing sixteen semi-structured interviews followed by Partial Least Squares Structural Equation Modeling (PLS-SEM) analysis of 101 survey questionnaires conducted in Iran using a hierarchical component model.
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The historical data of load, such as wind power data, are handled by using a hierarchical clustering algorithm and principal component feature extraction technology.
The R w wind power patterns is obtained using a hierarchical clustering algorithm combined with principal component-feature extraction technology with probability ( alpha_{{r_{w} }} ), denoted by ( (r_{w},alpha_{{r_{w} }} ) )((r_win {1,2,ldots,R_w})).
Components of variability were estimated using a hierarchical random effects analysis of variance (ANOVA) model.
Gene list similarities between tests are analyzed and visualized using a Hierarchical Clustering (binary metric and the Ward's aggregation algorithm, R package stats) and Principal Component Analysis (R package ade4 [25]).
Leader behaviour, however, is coded using a hierarchical format.
It relies on a hierarchical component based architecture.
It includes two major components: firstly, we use a hierarchical approach to improve computational efficiency and reduce dependency on a matching window size.
We use a hierarchical pathway representation model with a compound graph, and every pathway component in the INOH database is annotated by a set of uniquely developed ontologies.
That's why we use a hierarchical sales response model.
We used a hierarchical modeling approach.
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