The Clustering and Fuzzy Logic Methods Complex for Big Data Processing

Globa, Larysa; Novogrudska, Rina; Liashenko, Andrii

doi:10.25673/76934

Proceedings of International Conference on Applied Innovation in IT · 2022/03/09 · Vol. 10 · Issue 1 · pp. 69–79

The Clustering and Fuzzy Logic Methods Complex for Big Data Processing

Larysa Globa, Rina Novogrudska, Andrii Liashenko

📄 Download PDF DOI: 10.25673/76934

Abstract

Currently, telecom operators are facing a problem that is conditionally called "Big Data". The telecom industry is growing rapidly and dynamically, new technologies are emerging (IoT, M2M, D2D, P2P), new companies are using them, new information and communication services are being introduced to automate production processes, and so on. Methods of statistical analysis, A\B testing, data fusion and integration, Data Mining, machine learning, data visualization are used in the Big Data processing and analysis, but due to the fact that large amounts of Big Data are not structured, come in real-time with various delays related to bandwidth and network congestion, in each case the processes of processing and analysis of Big Data are extremely costly in terms of time and resources. As a result, telecom operators need not only to process large amounts of data but also to extract knowledge from them. However, the analytical processing of large data is characterized by blurred boundaries, which determine certain logical relationships between data. This

Keywords

Fuzzy Logic Clustering Algorithms Smart System Statistical Numerical Data Fuzzy Knowledge Bases

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