TARU PUBLICATIONS
Journal of Information and Optimization Sciences cover
Open Access ·Peer-reviewed·ISSN (Online): 2169-0103·ISSN (Print): 0252-2667

WoS  JIF 2026 : 0.4 (Q4)

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Monthly Journal: Publishes theoretical and applied research on topics in information and optimization sciences.

Issues up to 2022 co-published with and available at:Taylor & Francis
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Open Access Research Article

Leveraging machine learning for real-time optimization in large-scale information systems

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pp. 1289–1301Vol. 46Issue 4-BMay 2025DOI: 10.47974/JIOS-1990XML
Received:
09 Oct 2024
Published Online:
31 May 2025
Article type:
Research Article
Language:
EN
Article no.:
JIOS-1990
Pages:
1289–1301

Abstract

The quick development of information and the expanding complexity of large-scale data frameworks require progressed optimization methods to guarantee tall execution, versatility, and unwavering quality. Machine learning (ML) has developed as a effective apparatus for real-time optimization, advertising the capacity to memorize from tremendous sums of information and make data-driven choices with minimal human mediation. This term paper investigates the different applications of machine learning in optimizing large-scale data frameworks in genuine time, covering perspectives such as prescient analytics, peculiarity discovery, arrange activity administration, substance conveyance optimization, security, and personalized proposal frameworks. The paper points to supply a comprehensive outline of how machine learning can be utilized to upgrade the productivity, adaptability, and flexibility of these complex frameworks.

Keywords

Subject Classifications

68Q10

References

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