Neural network model to support decision-making on managing cooperative relations in innovative ecosystems

IF 0.4 Q4 MATHEMATICS, APPLIED Journal of Applied Mathematics & Informatics Pub Date : 2022-03-31 DOI:10.37791/2687-0649-2022-17-2-79-92
E. Kirillova, A. Lazarev, Oleg P. Kultygin
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引用次数: 2

Abstract

Currently, the specifics of external conditions and peculiarities of innovation activity main subjects development determine not only the need for close, long-term scientific and technical cooperation with the state for the sustainable development of territories, but also the need to develop and substantiate proposals for managing the development of innovation processes in such a system as a whole. The article proposes a model for the representation of scientific and industrial interaction in the implementation of regional innovation processes in the form of a three-dimensional "slice" of the triple helix as a resource VRIO-profile of cooperative formation, which allows to clearly demonstrate the system of relations, identify in which direction the problem area is, influencing which it will be possible to return the system to an equilibrium state of sustainable development in a strategic perspective. The analysis of modern scientific works shows the relevance, necessity and effectiveness of using methods based on neural networks to predict changes in the state of complex socio-economic systems, such as regional innovation systems. Existing approaches, as a rule, demonstrate a narrow focus and belonging to a separate enterprise or organization, and therefore do not meet all the requirements from both the implementation of the innovation process itself and the modification of the external environment. In this connection, the authors proposed an information and analytical solution for using the described model to support decision-making on the management of cooperative formations. The developed program is based on predicting the future state (position in a three-dimensional coordinate system) of the system using deep neural networks, namely recurrent. The described practical approbation of the model can in the future serve as a basis for decision-making on the choice of forms and directions of interaction of cooperative formations in the strategic perspective.
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支持创新生态系统合作关系管理决策的神经网络模型
目前,外部条件的特殊性和创新活动主体发展的特殊性,不仅决定了需要与国家进行密切、长期的科技合作,以实现领土的可持续发展,而且还需要在整个系统中制定和充实管理创新过程发展的建议。本文提出了一种以三螺旋的三维“切片”形式作为合作形成的资源VRIO-profile的形式来表示实施区域创新过程中的科学和产业互动的模型,该模型可以清楚地展示关系系统,确定问题区域的方向,从战略的角度来看,这将有可能使系统恢复到可持续发展的平衡状态。对现代科学工作的分析表明,使用基于神经网络的方法来预测复杂社会经济系统(如区域创新系统)状态变化的相关性、必要性和有效性。一般来说,现有的方法所关注的焦点较窄,属于单独的企业或组织,因此,无论是从创新过程本身的实施还是从外部环境的改变来看,都不能满足所有的要求。在此基础上,提出了利用所描述模型支持合作编队管理决策的信息分析解决方案。开发的程序是基于使用深度神经网络预测系统的未来状态(在三维坐标系中的位置),即循环。所描述的对模型的实际认可可以作为未来战略视角下合作编队互动形式和方向选择的决策依据。
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