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Principles of Creating Real-time Analytical Systems Based on Artificial Intelligence

Year: 2026

Type: article

Abstract: The rapid development of digital technologies has led to a dramatic growth in the volume of data generated across different sectors. Modern information systems must process and analyze these data streams quickly in order to support effective decision‑making. This article examines the principles of developing real‑time analytical systems based on artificial intelligence technologies. The research analyzes the role of machine learning algorithms and neural network models in processing large data streams, detecting hidden patterns, and generating predictive insights. Particular attention is paid to system architecture, scalability, data processing speed, and reliability. The study demonstrates that integrating artificial intelligence with real‑time data processing platforms significantly improves analytical capabilities and enables more accurate forecasting of complex processes.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.19564073

Authors: Karamatdinov, Abatbay, Rasulmukhamedov, Mukhamadaziz

Language: English

Topic: Data Stream Mining Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: green

OpenAlex ID: W7154347705

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