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September 2021 (published: 22.09.2021)
Number 3(46)
Home > Issue > Software-analytical tool for forecasting and evaluating the implementation of innovative processes in integration formations
Kirillova E.A. , Lazarev A.I.
The analysis of changes in the external and internal environment of organizations, requirements for ensuring long-term sustainability and competitiveness in modern conditions suggests the need to develop instrumental support for decision-making support processes in the implementation of innovative projects of cooperative formations. Significant expenditures of technical and time resources allow us to determine the priority problem – the insufficient development of systems for reducing uncertainty in interaction with the processes of scientific and industrial cooperation, which determine the disproportions of the resulting economic indicators of the functioning of innovative activity in the region. The purpose of this study was to develop a tool that allows solving this problem. During its implementation, the fuzzy logic apparatus, methods of analyzing and processing large, fuzzy data, the implementation of parallel analysis algorithms in cluster operating systems and the C Sharp programming language were used. The proposed solution is an implemented multiplatform software for neuro-cluster analysis of multiformat data, which is based on fuzzy data prediction algorithms based on a nonlinear autoregressive exogenous model. An important feature of the implemented software is an algorithm for optimizing the processing of predicted data, based on distributed analyzing of big data using Microsoft Server operating systems. The tool developed as a result of the study for evaluating the implementation of innovative processes will make it possible to increase the efficiency of the functioning of economic entities in the region by making management decisions based on the principles of optimality and balance of information in the implementation of innovative processes.
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Keywords: tools for supporting decision-making, interorganizational interaction, integration formations, scientific and industrial cooperation, neuro-fuzzy forecasting, clustering of big data.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
UDC 330.44: 338.43
Software-analytical tool for forecasting and evaluating the implementation of innovative processes in integration formations
The analysis of changes in the external and internal environment of organizations, requirements for ensuring long-term sustainability and competitiveness in modern conditions suggests the need to develop instrumental support for decision-making support processes in the implementation of innovative projects of cooperative formations. Significant expenditures of technical and time resources allow us to determine the priority problem – the insufficient development of systems for reducing uncertainty in interaction with the processes of scientific and industrial cooperation, which determine the disproportions of the resulting economic indicators of the functioning of innovative activity in the region. The purpose of this study was to develop a tool that allows solving this problem. During its implementation, the fuzzy logic apparatus, methods of analyzing and processing large, fuzzy data, the implementation of parallel analysis algorithms in cluster operating systems and the C Sharp programming language were used. The proposed solution is an implemented multiplatform software for neuro-cluster analysis of multiformat data, which is based on fuzzy data prediction algorithms based on a nonlinear autoregressive exogenous model. An important feature of the implemented software is an algorithm for optimizing the processing of predicted data, based on distributed analyzing of big data using Microsoft Server operating systems. The tool developed as a result of the study for evaluating the implementation of innovative processes will make it possible to increase the efficiency of the functioning of economic entities in the region by making management decisions based on the principles of optimality and balance of information in the implementation of innovative processes.
Read the full article
Keywords: tools for supporting decision-making, interorganizational interaction, integration formations, scientific and industrial cooperation, neuro-fuzzy forecasting, clustering of big data.
DOI 10.17586/2310-1172-2021-14-3-47-57