Abstract
Making informed decisions at the strategic level is rather complicated and requires a methodological and instrumental base due to the substantial size and heterogeneity of innovative scientific and industrial integration formations. The paper shows existing limitations on the tools used. The authors argue that their improvement with the use of fuzzy logic will enhance the effectiveness of decisions on the development of the region. Thus, the aim of the study is to develop a methodology for managing innovative processes of scientific and industrial structures based on the fuzzy sets theory. This will enable a more complete and clear representation of socio-economic systems. In this regard, it seems most appropriate to integrate fuzzy algorithms with the decision support system in the subject area of this work. To confirm the hypothesis, the authors describe the mechanism developed for managing innovation processes within a regional scientific and industrial cluster, using elements of the neural simulation framework. As an example confirming the hypothesis of the study, a feasibility analysis for the implementation of an innovative project within the cluster in the territory of the Smolensk region is given.
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The reported study was funded by RFBR, according to the research project No. 18-310-00222.
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Zaenchkovski, A.E., Kirillova, E.A., Golovinskaya, M.V., Sazonova, E.A., Borisova, V.L. (2021). Cognitive Fuzzy-Logic Modeling Tools to Develop Innovative Process Management Procedures for Scientific-Industrial Clusters. In: Bogoviz, A.V., Suglobov, A.E., Maloletko, A.N., Kaurova, O.V., Lobova, S.V. (eds) Frontier Information Technology and Systems Research in Cooperative Economics. Studies in Systems, Decision and Control, vol 316. Springer, Cham. https://doi.org/10.1007/978-3-030-57831-2_22
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