Semantic Scholar Open Access 2020 128 sitasi

Cognitive Technologies in the Management and Formation of Directions of the Priority Development of Industrial Enterprises

A. Kwiliński Aleksandra Kuzior

Abstrak

Abstract The possibilities of using cognitive technologies in the organization of systematic industrial enterprise management are described in the article. Strategic links are defined in the development of a system of stochastic models of enterprise management based on artificial intelligence. The possibility of introduction of the Perceptron model in the industrial enterprise management with the purpose of identification of “bottlenecks” in the functionality of business activity and improvement of procedures of decision-making in the framework of creation of the program of development and technical re-equipment of the enterprise is proven. The authors offered an organizational and economic mechanism of operation of an industrial enterprise, which includes new means of implementation of managerial actions through the use of a matrix of assessment of the level of implementation of cognitive technologies. The method of determining priority directions for the implementation of cognitive technologies at an enterprise was developed based on the results of the assessment of the depth of penetration of cognitive technologies and the result obtained from their implementation, which additionally takes into account the resource ratio of the implemented technologies defined as the ratio of estimates of the actual level of competencies to what is needed to work with new cognitive technologies, which allows to obtain the planned economic and organizational effect.

Topik & Kata Kunci

Penulis (2)

A

A. Kwiliński

A

Aleksandra Kuzior

Format Sitasi

Kwiliński, A., Kuzior, A. (2020). Cognitive Technologies in the Management and Formation of Directions of the Priority Development of Industrial Enterprises. https://doi.org/10.2478/mspe-2020-0020

Akses Cepat

Lihat di Sumber doi.org/10.2478/mspe-2020-0020
Informasi Jurnal
Tahun Terbit
2020
Bahasa
en
Total Sitasi
128×
Sumber Database
Semantic Scholar
DOI
10.2478/mspe-2020-0020
Akses
Open Access ✓