Open AccessSimulation of knowledge development in an innovation system based on neural network model
Author(s) -
Valery Soloviev,
В. Л. Розалиев
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2094/3/032044
Subject(s) - process (computing) , knowledge management , computer science , artificial neural network , state (computer science) , innovation system , sociology of scientific knowledge , management science , business , artificial intelligence , industrial organization , engineering , algorithm , operating system , philosophy , epistemology
Innovative development is impossible without the support of scientific research capable of forming fundamentally new technological approaches. The process of knowledge development cannot be fully formalized, therefore, management decisions are made in conditions of uncertainty. The models developed on the basis of self-organization are the most effective for predicting the development of knowledge in the innovation system. On the basis of the developed recurrent neural network, the analysis of the influence of the state scientific and technical policy on the formation of the strategies of the actors of the national innovation systems of the BRICS countries is carried out. The determinants of the influence of the state scientific and technical policy on the development of knowledge in the innovation system are revealed.