Deep Hybrid Model for fault diagnosis of ship's main engine

LiteFDNet: A lightweight network for current sensor-based bearing fault diagnosis

Deep learning-based hybrid feature extraction for bearing fault diagnosis

Weighted Distance-Based Meta-Learning Model for Anomaly Detection in Assembly Process

(submitted) A Machine Learning Ensemble Framework Based on a Clustering Algorithm for Improving Electric Power Consumption Performance

(submitted) Deep learning-based hybrid feature extraction for bearing fault diagnosis

(submitted) Weighted Distance-Based Meta-Learning Model for Anomaly Detection in Assembly Process.

Enhanced data processing and machine learning techniques for energy consumption forecasting

A novel framework integrating ensemble transfer learning and ant colony optimization for knee osteoarthritis severity classification

Data-driven resource allocation for deep learning in IoT networks