Analysis of Probabilistic Distributions and Uncertainty of Information Flow at Administrative Workflows

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Analysis of Probabilistic Distributions and Uncertainty of Information Flow at Administrative Workflows

February 25, 2020 Mathematical Science MATHEMATICS 0

Common methods found in the market such as LEAN, AGILE, SCRUM are short and insufficient to generate a high level of efficiency in discrete-continuous variables based workflows and aspects of classification, decidability and analysis remains mostly copies of successful cases. The new metric and theoretical framework proposed in this article allows qualitative classification and analysis of workflows in close proximity to qualitative theory of differential equations (QDE), raising the possibility of fulfill the gaps existent in the commercial and popular methods. These metrics are also the result of research carried out in the view of the difficulty of characterizing the solidity aspect of workflows and enabling continuous improvements as a complex adaptive system (CAS).

Creative Commons Attribution License: This article was originally published in its full content in Journal of Mathematics, 2019 (Hindawi): “A Mathematical Modelling for Workflows” and it was republished as a book chapter (SCIENCEDOMAIN International) under the title “Analysis of Probabilistic Distributions and Uncertainty of Information Flow at Administrative Workflows” with some small modifications from the previous version.

Author(s) Details

Charles Roberto Telles
Department of Research Advisory, Secretary of State for Education and Sport, Curitiba, Paraná, Brazil.

View full book: http://bp.bookpi.org/index.php/bpi/catalog/book/140

 

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