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Intelligent cell analysis in 5G/B5G using TOPSIS and ML | ||
| Future Research on AI and IoT | ||
| مقالات آماده انتشار، اصلاح شده برای چاپ، انتشار آنلاین از تاریخ 24 خرداد 1405 اصل مقاله (721.22 K) | ||
| نوع مقاله: Research Article | ||
| شناسه دیجیتال (DOI): 10.22080/frai.2026.30812.1042 | ||
| نویسندگان | ||
| Reza Moammer Yami* 1؛ Hadi Soltanizadeh2؛ Ali Shahzadi3 | ||
| 1Department of Electrical Engineering, Semnan University, Semnan, Iran | ||
| 2Associate Professor, Department of Electronics @ Faculty of Electrical and Computer Engineering,semnan.iran | ||
| 3Associate Professor, Department of Electronics @ Faculty of Electrical and Computer Engineering.semnan.iran | ||
| تاریخ دریافت: 28 آذر 1404، تاریخ بازنگری: 21 اردیبهشت 1405، تاریخ پذیرش: 24 خرداد 1405 | ||
| چکیده | ||
| The aim this research is to accurately rank and increase the accuracy of abnormal cell detection in 5G and B5G networks by combining machine learning (ML) algorithms with TOPSIS multi-criteri decision-making (MCDM) technique. This study was conducted in two main stages: ranking stage and failure estimation and detection stage. In the first stage, TOPSIS technique was used to rank and score and identify the best and worst cells. In the second stage, supervised ML algorithms were used to predict and estimate defective cells. The results show that this hybrid approach effectively addresses the challenges of data quality, scalability, complexity and real-time processing , error interpretation is also able to classify the types of failures of each cell. Specifically, AdaBoost achieved 98.886% accuracy, 0.978 precision and 0.989 F-Measure, while logistic regression achieved 97.7881% accuracy, 0.968 precision and 0.979 F-Measure, both excellent failures. TOPSIS technique provides network operators with transparency and interpretability of each cell's performance by selecting and weigh assignment all the Indicators that affect the performance of each cell. This study represents a critical breakthrough in increasing the reliability, efficiency and scalability of next-generation networks, thereby providing greater intelligence and agility in network operations | ||
| کلیدواژهها | ||
| MCDMA؛ TOPSIS؛ Cell Fault Detection؛ SON؛ 5G &B5G | ||
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آمار تعداد مشاهده مقاله: 0 تعداد دریافت فایل اصل مقاله: 1 |
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