The ability to understand results using predictive models as a tool can
be critical to the application and the performance based on
determination according to the predictions by supporting a feasible
method. j The suitability to offer a predictive modeling approach for
characterization allows to identify how an analytical roadmap can
serve as guide to describe the model results according to the data set
implemented. The evaluation of the suitable characteristics pertaining
to the data set can be described by the constraints in a workload
environment. The parameters to create an investigative framework to
examine the environment includes the ability to capture each factor.
This investigative framework allows for the examination of the
significant change in degree of differences. j The impact of transition
segment measures includes the ability to address cognitive awareness,
systems awareness, and performance awareness. j The probability
measures regarding degree of differences are evaluated according to
the matrix results for attention to environmental workload capturing
and identifying intensity of the control laws inputs related to the
degree rates. These measures related are characterized to understand
the practical activities intensity of control laws (e.g., low intensity,
medium intensity and/or high intensity).
