DocumentCode :
3588877
Title :
Communality Performance Assessment of Electricity Load Management Model for Namibia
Author :
Asemota, Godwin Norense Osarumwense
Author_Institution :
Electr. & Electron. Eng. Dept., Univ. of Rwanda, Kigali, Rwanda
fYear :
2014
Firstpage :
252
Lastpage :
257
Abstract :
This paper, "Communality performance assessment of electricity load management model for Namibia", presents a good analysis of the interval of communality. While there is only a minimum, which strengthens the author\´s claim of obtaining the optimal performance assessment criterion for the electricity load management model developed. Out of the 300 administered questionnaires, 127 were yielded for statistical analyses. The separate communalities obtained closely mirrored the predictors, whenever they were closer to unity. Using Borel\´s strong law of large numbers for analyses, it was shown that sample sizes larger than 127, produced errors, which exceeded 0.1 only once for every five runs of the process. Therefore, communality analyses provide elegant lower-bound solutions that belong to a class of nonsmooth optimisation algorithms useful for obtaining high quality exploratory and confirmatory decoupled multivariate analyses, as shown in this study.
Keywords :
load management; optimisation; statistical analysis; Namibia; communality analyses; communality performance assessment; confirmatory decoupled multivariate analyses; electricity load management model; nonsmooth optimisation algorithms; statistical analyses; Analytical models; Buildings; Eigenvalues and eigenfunctions; Load management; Load modeling; Loading; Reliability; collinearity; data reduction; factor loading; hypotheses testing; Kaiser criterion; latent variables; scree;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Intelligence, Modelling and Simulation (AIMS), 2014 2nd International Conference on
Print_ISBN :
978-1-4799-7599-0
Type :
conf
DOI :
10.1109/AIMS.2014.20
Filename :
7102469
Link To Document :
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