The Babylonian Journal of Machine Learning (BJML) (EISSN: 3006-5429) is a specialized publication dedicated to the exploration and integration of modern machine learning methodologies. As a platform for researchers and scholars, the journal focuses on the intersection of cutting-edge advancements in machine learning. Through high-quality articles, it fosters interdisciplinary discussions aimed at propelling forward the field of machine learning research.

Current Issue

Vol. 2026 (2026)

 

 

Published: 2026-01-10

Articles

Cross-Layer Co-Design and Physics-Grounded Evaluation of Hybrid Reinforcement Learning and Federated ANN-PID Protocol Suites for Dense Urban UAV Delivery Networks

Randa Shaker Abd-Alhussain, Qasim Radam Mahmood, Hasan Mohammed Taqi Salih Albdair, Mohammad Khaleel Sallam Ma’aitah, Sanad Abdullah Alafghani, Ashraf Al-Shaikh Khalil, Ashraf Zaher

164-196

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Effective Android Malware Detection Using CNN and LSTM Model with GWO-Based Feature Selection

Hawraa.O. Musa, Muhanad.T. Younis

1-22

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An Explainable Hybrid GWO-LightGBM Model for Breast Cancer Diagnosis Using SHAP Interpretation

Ahmed Aljuboori, Hamsa M Ahmed, M. M. A. Abdulrazzq

23-36

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MOGNN-EC: A Multi-Objective Optimization Framework for Efficient Energy Management and Charging Coordination in Electric Vehicle Networks

Yaseen Ali Sahood, Najlaa Nsrulaah Faris, Ahmed Rashid Alkhuwaylidee, Ahmed Saihood

37-60

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HGS-RF: A Heuristic-Guided Selective Random Forest for Multi-Label Vulnerability Detection in Smart Contracts

Saad Nasser AlAzzam , Ghassan ALDharhani, Raenu ALKolandaisamy

61-94

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An AI-Driven Intrusion Detection and Real-Time Autonomous Response Framework Using Network Traffic Logs: AMulti-Algorithm Approach with LightGBM Optimization

Ahmed Sileh Gifal, Hussein Mohammed Ali Makassees, Mayameen S. Kadhim, Ahmed Dheyaa Radhi, Rusul Mansoor Al-Amri, Liaw Geok Pheng

95-109

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A Preemptive Ensemble Learning Framework for KnowledgeBased Network Intrusion Detection

Maad Kamal Al-anni, Ammar A Al-Hamadani, Rafah M. Almuttairi, Alharith A Abdullah

110-130

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Deep Learning-Based Pre-Processing Pipeline and Hybrid Vision Transformer Model for Deepfake Video Detection

Harith A. Hussein, Khalid Shaker, Salwani Abdullah

131–163

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