Abstract
This paper addresses the issue of creating the methodology that could help to answer the question about assessing the effects of a given export policy. The new approach for constructing and calculating the import countries ranking is proposed. The peculiarity of such problems lies in the weakly formalised set of factors that define the import rank of every country. The question is also complicated by the excessive flow of information which may be unreliable and contradictory. Therefore, the possibilities of statistical methods to support the solution of such a problem are limited. To forecast and support export solutions for the short and medium term, the concept of “Rank of the country’s import priority” (Priority Index, PI) is introduced. It is built on historical data with applying the econometric methods. For the medium and long-term perspective and for taking into account non-quantitative factors, it is suggested using the methods of networked expertise (e-expertise), cognitive modelling, artificial intelligence (AI), inverse problems solving on cognitive model with genetic algorithms, and Deep Learning.
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Acknowledgment
This work is partially funded by the Russian Ministry of Agriculture, the State contract 497/12-SK of 07.12.2017; Russian Science Foundation, Grant 17-18-01326; Russian Foundation for Basic Research, grant 18-29-03086.
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Raikov, A., Abrosimov, V. (2018). Import Countries Ranking with Econometric and Artificial Intelligence Methods. In: Alexandrov, D., Boukhanovsky, A., Chugunov, A., Kabanov, Y., Koltsova, O. (eds) Digital Transformation and Global Society. DTGS 2018. Communications in Computer and Information Science, vol 858. Springer, Cham. https://doi.org/10.1007/978-3-030-02843-5_32
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DOI: https://doi.org/10.1007/978-3-030-02843-5_32
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