Technique of the Joint Use of System Dynamics and Cognitive Analysis for Reengineering of Complex Economic and Social-Political Systems

The technique of the joint use of system dynamics and cognitive analysis for reengineering of complex systems has been proposed. The use of the system dynamics technique at the initial stage of reengineering processes faces the certain difficulties due to the fact of presence of large amount of parameters.It is rather difficult to choose correctly all levels’ and variables’ initial values and change rates. Arbitrary assignment of initial values leads to radical incorrect reengineering procedures. In order to avoid this undesirable result the approach presented in the article assumes the implementation of the cognitive analysis technique at the initial stage. After revelation of fundamental trends of development and screening of insignificant factors system dynamics methodology is proposed to be implementedcognitive analysis, system dynamics, reengineering, impulse oriented weighted graphs, qualitative assessment of processes, emergency management

Economic Growth in Georgia: Historical Perspectives and Prognosis

While output declined in virtually all transition economies in the initial years, the speed and extent of the recovery that followed has varied widely across these countries. The paper examines some aspects of transition experiences of 1990s and dynamics of GDP in Georgia during transition recession and following post-recession recovery. Economic growth is considered as complex and comprehensive phenomenon. The prognostic econometric model of Georgian GDP is developed.economic growth, GDP, transitional economy, Georgia, prognostic model, regression, non –linear trend

Economic growth in Georgia: Historical perspectives and prognosis

While output declined in virtually all transition economies in the initial years, the speed and extent of the recovery that followed had varied widely across the transition countries. The paper examines some aspects of transition experiences of 1990s and the dynamics of GDP in Georgia during transition recession and following post-recession recovery. GDP prognostic econometric model for Georgia is developed

The Generalized Technique for Evaluation of Quality Level of Manufacturing, Business and Educational Processes

The requirements for production and learning process quality are different in various manufacturing, business and educational organizations. A new approach to fit these requirements and evaluate the closeness of realistic(actual) quality of production or learning processes (based on quality indicators of output or scores of examination tests) is proposed in the paper. The technique uses the strictly defined approximation procedures and allows users automatically evaluate closeness of actual quality level when quality requirements change.</jats:p

Evaluation of quality level and selection of relevant parameters&apos; values in manufacturing, business and education

Abstract- The requirements for production and learning process quality are different in various manufacturing, business and educational organizations. A new approach to fit these requirements and evaluate the closeness of realistic (actual) quality of production or learning processes (based on quality indicators of output or scores of examination tests) is proposed in the paper. The technique uses the strictly defined approximation procedures and allows users automatically evaluate of closeness of actual quality level when changing quality requirements. In case of significant difference between actual and pattern distributions a new approach (using neural network of &apos;Generalized Regression Neural Network&apos; type) of determining the minimum values of the factors that will bring the actual distribution to the pattern one is proposed in the paper. Keywords: manufacturing processes quality, business processes quality, learning process quality, percentile function, non-parametric approximation, generalized lambda distribution, Generalized Regression Neural Networks (GRNN). I. Introduction Let&apos;s assume that we are given the next requirement for the learning process quality: &quot;weak&quot; (failed) students can be thought those ones whose grades are less than 60 and the percentage of them should be 30%; &quot;ordinary&quot; (of acceptable level) students are those ones whose grades are between 61 and 95 grades, the percentage of them should be 65%; in latter range so called &quot;middle&quot; level students are those whose percentage is no more than 50% of total number of students (including failed ones) and 20% of &quot;ordinary&quot; student; say, the grade of these &quot;middle&quot; students turns out to be 80 ( or any other value), so the grade 80 can be considered as a median of grades distribution; &quot;excellent&quot; students are those ones whose grades are above 95% and the percentage of them is 5%. The corresponding cumulative distribution function (CDF) is shown i