Subject. This article focuses on the issues of neural network modeling of innovative development. Objectives. The article aims to study the process of neural network modeling of the innovative development of the electronics industry in the regions of Russia. Results. The article presents the author-developed methodology for neural network modeling of the innovative development of the electronics industry of the regions. Conclusions and Relevance. The results obtained can be useful for government agencies to plan support for the innovative development of the electronics industry in regions. Investors can also use these results to choose the area of capital investment of their funds.
Keywords: neural network, time series, prediction, radio electronics industry
References:
Dobrova K.B., Sakhnenko S.S. [Radio-electronic industry enterprises in the structure of the high-tech sector of the economy]. Ekonomika: vchera, segodnya, zavtra = Economics: Yesterday, Today and Tomorrow, 2022, vol. 12, no. 10A, pp. 240–246. URL: Link (In Russ.)
Trofimov O.V., Ganin A.N. [Development of acceleration program for startups in the electronic industry]. Kreativnaya ekonomika = Journal of Creative Economy, 2019, vol. 13, no. 3, pp. 553–558. (In Russ.) URL: Link
Chen W., Huang X., Liu Y., Song Y. Does Industry Integration Improve the Competitiveness of China’s Electronic Information Industry? – Evidence from the Integration of the Electronic Information Industry and Financial Industry. Sustainability, 2019, vol. 11, no. 9, 2695. URL: Link
Klushantsev D.V. [The evolution of the industrial specialization of the radio electronics industry of Saint-Petersburg]. MIR (Modernizatsiya. Innovatsii. Razvitie) = MIR (Modernization. Innovation. Research), 2020, vol. 11, no. 1, pp. 59–71. URL: Link (In Russ.)
Balychev S.Yu., Bat'kovskii M.A., Kravchuk P.V., Sudakov V.A. [Optimization of diversification programs of enterprises of the radio electronic industry]. Nauka bez granits, 2020, no. 2, pp. 27–32. (In Russ.) URL: Link
Cholid I., Robiani B. Analysis in Productivity and Efficiency on Computer and / or Assembly in Electronic Computer and Computer Device Industries in Indonesia 2011–2015 (ISIC 26210 and 26210) Proceedings of the 5th Sriwijaya Economics, Accounting, and Business Conference (SEABC 2019), 2020, pp. 48–51. URL: Link
Vadavalasa R. Controlling and Monitoring Semiconductor Manufacturing Process Using Smart Technologies. International Research Journal of Modernization in Engineering Technology and Science, 2020, vol. 02, iss. 07, pp. 147–164. URL: Link
Fu Haw Ho, Salwa Hanim Abdul-Rashid, Raja Ariffin Raja Ghazilla et al. What Key Drivers Are Needed to Implement Material Efficiency Strategies? An Analysis of the Electrical and Electronic Industry in Malaysia and Its Implications to Practitioners. Sustainability, 2021, vol. 13, iss. 4, 2065. URL: Link
Shu-Chuan Chen, Da-Sheng Lee, Chien-Yi Huang. Evaluating the Sustainable Operating Performance of Electronics Industry Groups: Taiwanese Firms in Mainland China. Sustainability, 2021, vol. 13, iss. 21, 12030. URL: Link
Yu Wang, Junwei Li, Shen Zhong. Analysis on the Innovation Efficiency of China's Electronic and Communication Equipment Industry. Journal of Radiation Research and Applied Sciences, 2022, vol. 15, iss. 1, pp. 111–121. URL: Link
Gautam M., Ben-Idris M. Optimal Sizing of Movable Energy Resources for Enhanced Resilience in Distribution Systems: A Techno-Economic Analysis. Electronics, 2023, vol. 12, iss. 20, 4256. URL: Link
Tawfik S.A., Isayev O., Stampfl C. et al. Efficient Prediction of Structural and Electronic Properties of Hybrid 2D Materials Using DFT and Machine Learning. Advanced Theory and Simulations, 2019, vol. 2, iss. 1, 1800128. URL: Link
Hyeonmin Kim, Young Yoon. An Ensemble of Text Convolutional Neural Networks and Multi-Head Attention Layers for Classifying Threats in Network Packets. Electronics, 2023, vol. 12, iss. 20, 4253. URL: Link
Haoyang Shi, Xing Zhang, Peixuan Wu et al. ComEdge: Cloud-Native Platform for Integrated Computing and Communication in Satellite–Terrestrial Network. Electronics, 2023, vol. 12, iss. 20, 4252. URL: Link
Bláha Z. Redefining Intelligence: The Fusion of AI and Mechatronics. Journal of Industrial Electronics and Applications, 2023, vol. 7, iss. 2.
Yue Hou Maria. Integrating Industrial Informatics and Computational Intelligence for Smart Manufacturing. Journal of Industrial Electronics and Applications, 2023, vol. 7, iss. 1. URL: Link
Feng H.-Z., Yu H.-Y., Wang W.-Y. et al. Recognition of Mortar Pumpability via Computer Vision and Deep Learning. Journal of Electronic Science and Technology, 2023, vol. 21, iss. 3, 100215. URL: Link
Zhan J.-Y., Yu A.-T., Jiang W. et al. FPGA-Based Acceleration for Binary Neural Networks in Edge Computing. Journal of Electronic Science and Technology, 2023, vol. 21, iss. 2, 100204. URL: Link
Wu B., Hao Zh.-L., Chen J.H. et al. Total Transmission from Deep Learning Designs. Journal of Electronic Science and Technology, 2022, vol. 20, iss. 1, 100146. URL: Link
