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Knopik, L., & Bojar, W. (2013). Mozliwosci zastosowania metody wielo – agentowej w analizie wybranych modeli (Possibilities of multiagent appliacation for analysis of selected models). In K. Rostek (Ed.), (pp. 199–208). Zarzadzanie wiedza w tworzeniu przewagi konkurencyjnej (Knowledge management in creating comparative advantage). Warsaw: Warsaw Technical University.
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Bojar, W., & Knopik, L. (2014). Application of Markov chains approach for expecting extreme precipitation changes having impact on food supply..
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Bojar, W., Knopik, L., & Zarski, J. (2013). Analiza wplywu warunków klimatycznych na plonowanie roslin uprawnych w regionie kujawsko-pomorskim (Analysis of impact of climate conditions on yielding of crops in Kujavian & Pomeranian region) (Vol. 64).
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Bojar, W., Żarski, J., Knopik, L., Kuśmierek-Tomaszewska, R., Sikora, M., & Dzieża, G. (2016). Markov Chain as a Model of Daily Total Precipitation and a Prediction of Future Natural Events.. Berlin (Germany).
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Bojar, W., Knopik, L., Żarski, J., & Kuśmierek-Tomaszewska, R. (2016). Integrated assessment of crop productivity based on the food supply forecasting. Agricultural Economics – Czech, 61(11), 502–510.
Abstract: Climate change scenarios suggest that long periods without rainfall will occur in the future often causing instability of the agricultural products market. The aim of our research was to build a model describing the amount of precipitation and droughts for forecasting crop yields in the future. In this study, we analysed a non-standard mixture of gamma and one point distributions as the model of rainfall. On the basis of the rainfall data, one can estimate parameters of the distribution. Parameter estimators were constructed using a method of maximum likelihood. The obtained rainfall data allow confirming the hypothesis of the adequacy of the proposed rainfall models. Long series of droughts allow one to determine the probabilities of adverse phenomena in agriculture. Based on the model, yields of barley in the years 2030 and 2050 were forecasted which can be used for the assessment of other crops productivity. The results obtained with this approach can be used to predict decreases in agricultural production caused by prospective rainfall shortages. This will enable decision makers to shape effective agricultural policies in order to learn how to balance the food supplies and demands through an appropriate management of stored raw food materials and import/export policies.
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