Complexity of the agricultural business tasks, high dynamism and non-linear nature of the contemporary socio-economic processes which differs functioning of any industry are placing new requirements for predictive studies. The purpose of this study is to develop a set of methodological provisions for the construction of predictive scenarios of the agricultural business by identifying current trends, the impact factors of the environment and the interpretation of results forecasting and analytical calculations. This article considers the influence of climatic factors on the economic impact of the frumentaceous and the grape branches of agriculture. The system of economic and mathematical prognostics models of the main industrial indicators was developed. The methodology for scenario forecasting of indicators of frumentaceous production and vine growing was proposed based on the use of the influence of solar activity on agrobiological processes.
The purpose of this research is to form a set of methodological provisions related to the use of cognitive modeling in the management of complex systems in conditions of high dynamism of studied processes. The rapid development of information and analytical tools provides new opportunities for applying cognitive modeling to a wider range of systems. The methodological basis of the study is the system methodology and its direct implementation is based on the system sequence “mission – goal – functions - structure – behavior – result”. Cognitive modeling in the management of complex systems takes into account their hierarchical structure, which entails the hierarchy of the corresponding models, which is directly reflected in the generated models or considered when building local models for systems of a certain hierarchy level. Complex systems also determine the complexity of the models that represent them. Therefore, the paper proposes stratification of the modeling process and its results on five levels: the representation model, the understanding model, the interaction model, the management model and the behavior model. The dynamics of simulated systems and their external environment assumes an iterative (cyclic) nature of cognitive modeling. The paper presents a structural cognitive model of managing the functioning and development of complex systems as its result.
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