PIECEWISE LINEAR ECONOMIC-MATHEMATICAL MODELS WITH REGARD TO UNACCOUNTED FACTORS INFLUENCE IN 3-DIMENSIONAL VECTOR SPACE
Abstract
This paper builds upon the foundation established in prior publications [1-5, 12], which introduced the theory of constructing piecewise-linear economic mathematical models within finite-dimensional vector spaces, accounting for the impact of unaccounted factors. These models offer a promising framework for predicting and managing economic processes under conditions of uncertainty, providing a means to define economic process control functions within multidimensional vector spaces.
However, it is essential to acknowledge the inherent challenges in addressing uncertainty within economic processes. The lack of a precise definition for "uncertainty" in economic contexts, incomplete classifications of its manifestations, and the absence of a clear mathematical representation contribute to the complexity of solving predictive and control problems. The economic landscape is characterized by multidimensionality and spatial heterogeneity, compounded by the temporal variability of multifactor economic indicators and their changing rates.
This paper navigates these complexities and uncertainties, offering insights and methodologies to elevate the solution of economic process prediction and control problems to a higher level of sophistication.
Keywords:
Piecewise-linear models, economic mathematical models, uncertainty, economic processes, multidimensionalityDownloads
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Copyright (c) 2023 Elchin Mammadov
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