{"id":2851,"date":"2024-02-12T12:22:54","date_gmt":"2024-02-12T09:22:54","guid":{"rendered":"https:\/\/nor-ijournal.com\/?p=2851"},"modified":"2024-02-15T19:44:15","modified_gmt":"2024-02-15T16:44:15","slug":"126-22","status":"publish","type":"post","link":"https:\/\/nor-ijournal.com\/ru\/2024\/02\/12\/126-22\/","title":{"rendered":"Ryzhov A. – IMPROVING THE DECISION-MAKING SYSTEM BY APPLYING MACHINE LEARNING ALGORITHMS IN A TELECOMMUNICATIONS COMPANY"},"content":{"rendered":"
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IMPROVING THE DECISION-MAKING SYSTEM BY APPLYING MACHINE LEARNING ALGORITHMS IN A TELECOMMUNICATIONS COMPANY<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Ryzhov A.
<\/strong>Georgia, Adjara region, city Makhinjauri, str. Israfil Jincharadze, h.3, app. 611<\/em><\/p>

Abstract
<\/strong>Currently, artificial intelligence (AI) is actively used in many fields, including the telecommunications industry. Machine learning (ML) algorithms play a key role in automation, classification, segmentation, and clustering tasks to support decision-making systems (Jepsen 2021). ML algorithms are introduced to achieve classified product offers in the accounting system, thereby building the company’s financial statements. This study solves the problem of automating a business process by using ML algorithms.
One of the most significant technological advances of the last decade has been the development and widespread adoption of ML. Decision-making systems using ML algorithms can be applied in various areas for intelligent decision-making to minimise manual human labour in business processes.
Various tasks were identified to achieve the study\u2019s goal. They included analysing the company\u2019s existing business processes, identifying bottlenecks and shortcomings, developing KPIs to measure its effectiveness, and proposing a new solution for organising the business processes.
This research proposes a model that automates manual labour. This model is a technical solution for making changes to an existing information system, supporting the operation of an ML model, and using the prediction results in an automated business process.<\/p>

Keywords:<\/strong> machine learning, decision-support system, improving information system, ML models, classification, ML algorithms, refactoring business process, artificial intelligence<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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