Analysis and design of multicomponent systems in biotechnology industry in the context of uncertainty based on entropy potential quality indicators
Annotation
The article deals with the approach to the analysis and design of formulations for multicomponent systems in the context of a priori uncertainty due to "deficiency" of information to measure the quality of raw materials and products. This situation is typical for many processes and industries in biotechnology industry. It results firm the instability of the composition and properties of the raw materials used, and the difficulty and expensiveness of measuring individual indicators. To solve the problems in question it is proposed to use the models for the states of uncertainty based on entropy potentials of the analyzed indicators. Also, methodological and computational aspects of determining the parameters of the models in different situations with the original data are discussed. The prospects for the use of the models for monitoring and control are analyzed.
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