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Modeling of transformation of technological development using two-dimensional neural self-organizing maps

Vol. 25, Iss. 1, JANUARY 2019

Received: 16 August 2018

Received in revised form: 26 September 2018

Accepted: 10 October 2018

Available online: 29 January 2019


JEL Classification: O30

Pages: 228–246

Zabolotskii A.A. Institute of Economics and Industrial Engineering, Siberian Branch of RAS (IEIE SB RAS), Akademgorodok, Novosibirsk, Russian Federation

Subject This article discusses the issues of technological development, namely its limits, influencing the economic and innovation growth.
Objectives The article aims to study and prove the existence of the limits of technological development.
Methods The research uses an innovative method of forecasting on the basis of weight vectors of neural self-organizing maps (SOM).
Results The article explores the transformation of investment and the changing structure of innovative progress that has led to this transformation. It shows two main factors, namely the limit of scientific breakthrough and the technological limit that influence the transformation. The article also models the process of generating scientific breakthroughs using a two-dimensional self-organizing map neural network (MATLAB neural clustering tool), and on the basis of these results, it makes predictions up to 2050.
Conclusions and Relevance The neural network weight map can be used to model and forecast evolutionary systems, as well as for accurate forecasting of technologies that may appear in the future, or can show the exhaustion of the potential of innovative development for these input component sets and technologies.

Keywords: limit to growth, drastic innovation, technological limit, forecasting, Schumpeterian waves


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