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Assessment of the Sustainability of Agricultural Production in the Region on the Basis of Five-Level Fuzzy [0,1] – Classifier

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13th International Conference on Theory and Application of Fuzzy Systems and Soft Computing — ICAFS-2018 (ICAFS 2018)

Abstract

The technique of estimation of stability of agricultural production in the region on the basis of standard multilevel fuzzy [0,1] – classifiers is offered. The methodology makes it possible to form a comprehensive sustainability of agricultural production in the region based on the factors of three groups: economic, social and environmental sustainability. The resulting estimate is based on aggregation of estimates for each of the three listed areas. Evaluation of each area is based on the aggregation of the assessments of the mixed complex indicators. Aggregation is performed on the basis of time series of numerical values of heterogeneous indicators reflecting both the level and growth rates of indicators for the studied periods. The contribution of each of the indicators is estimated using a weighting factor reflecting its importance. The advantages of the proposed evaluation methodology in comparison with the existing methods consist in a simple scheme of calculations, taking into account a large number of heterogeneous significant indicators, allowing for variation depending on the available statistical material and features of a specific practical problem. It is adaptable and versatile, allowing it to be applied to assess the intensity of not only agricultural but also industrial production on various scales.

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Correspondence to Elizabeth A. Arapova .

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Arapova, E.A., Denisov, M.Y., Ivanova, E.A., Kulikova, Y.V. (2019). Assessment of the Sustainability of Agricultural Production in the Region on the Basis of Five-Level Fuzzy [0,1] – Classifier. In: Aliev, R., Kacprzyk, J., Pedrycz, W., Jamshidi, M., Sadikoglu, F. (eds) 13th International Conference on Theory and Application of Fuzzy Systems and Soft Computing — ICAFS-2018. ICAFS 2018. Advances in Intelligent Systems and Computing, vol 896. Springer, Cham. https://doi.org/10.1007/978-3-030-04164-9_89

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