USE OF INTELLIGENT INFORMATION SYSTEMS IN ENTERPRISE MANAGEMENT AND DECISION-MAKING

Авторы

  • Dildora Davlatova Nordic international university

Ключевые слова:

Artificial intelligence, corporate enterprise, intellectual analysis, information systems, structured and unstructured data, integration.

Аннотация

This article discusses the use of modern information systems in the management of corporate enterprises. In particular, the basics of using information systems in the data mining of an enterprise based on artificial intelligence in the process of digitalization of the economy are set out on the example of the program 1-C Enterprise 8.3. Currently, due to the fact that enterprises have a very large flow of information, the process of managing such corporate enterprises and making decisions in them remains a very complex process. In the face of increasing uncertainty, business increasingly requires new, high-quality methods and tools that allow automatic data search based on previously incomprehensible algorithms and rules and identify unknown parameters. This will become the basis for the creation and implementation of new intelligent information systems based on artificial intelligence for enterprises. In this context, the article examines the role and importance of information systems based on artificial intelligence in deterministic, unstructured and weakly structured situations in the process of management and decision- making in corporate enterprises.

Библиографические ссылки

Decree of the President of the Republic of Uzbekistan on February 7, 2017 Appendix 1 to Decree No. PF-4947 "On the Strategy of Actions for Further Development of the Republic of Uzbekistan". www.lex.uz.

Чернышова Г.Ю. Интеллектуалный анализ данных: учеб. пособие для студентов специалности 080801.65 «Прикладная информатика (в экономике)» - Саратовский государственный социално- экономический университет. – Саратов, 2012. – 92 с.

Афанасева С.В. Технология интеллектуалного анализа данных: учеб. пособие – М.:Нац. исслед. ун-т «Высшая школа экономики», 2013. – 152 с.

Chandola, V., Banerjee, A., & Kumar, V. (2009). Anomaly detection: A survey. ACM Computing Surveys, 41(3), 1-58.

Ahmed, M., Mahmood, A. N., & Hu, J. (2016). A survey of network anomaly detection techniques. Journal of Network and Computer Applications, 60, 19-31.

Breunig, M. M., Kriegel, H.-P., Ng, R. T., & Sander, J. (2000). LOF: Identifying density-based local outliers. Proceedings of the 2000 ACM SIGMOD International Conference on Management of Data.

Pimentel, M. A. F., Clifton, D. A., Clifton, L., & Tarassenko, L. (2014). A review of novelty detection. Signal Processing, 99, 215-249.

Davlatova, D. (2023). MENEJERLARNING TASHKILOT QARORLARINI QABUL QILISHDA SUN’IY INTELLEKTDAN FOYDALANISH. INNOVATIVE DEVELOPMENT IN THE GLOBAL SCIENCE, 2(7), 65-68.

Davlatova, D. (2023). MENEJERLAR UCHUN SUN’IY INTELEKTNING BILIM ASOSLARI. Interpretation and researches, 1(14).

Загрузки

Опубликован

2024-12-16

Выпуск

Раздел

Образовательные статьи

Наиболее читаемые статьи этого автора (авторов)