• 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