Comparative analysis of the performance of supervised learning algorithms for photovoltaic system fault diagnosis, Eldeghady, Ghada Shaban, Kamal Hanan Ahmed, and Hassan Mohamed Moustafa A. , Science and Technology for Energy Transition, Volume 79, p.27, (2024) Abstract
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A hybrid model of CNN and LSTM autoencoder-based short-term PV power generation forecasting, Ibrahim, Mohamed Sayed, Gharghory Sawsan Morkos, and Kamal Hanan Ahmed , Electrical Engineering, p.1–17, (2024) Abstract
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Fault diagnosis for PV system using a deep learning optimized via PSO heuristic combination technique, Eldeghady, Ghada Shaban, Kamal Hanan Ahmed, and Hassan Mohamed Moustafa A. , Electrical Engineering, Volume 105, Number 4, p.2287–2301, (2023) Abstract
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Performance Comparison of Multiple Neural Networks for Fault Detection of Sensors Array in Oil Heating Reactor, Mustafa, Mai, Gharghory Sawsan Morkos, and Kamal Hanan Ahmed , International Journal of Advanced Computer Science and Applications, Volume 13, Number 12, (2022) Abstract
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SDC-Net: End-to-End Multitask Self-Driving Car Camera Cocoon IoT-Based System, Abdou, Mohammed, and Kamal Hanan Ahmed , Sensors, Volume 22, Number 23, p.9108, (2022) Abstract
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End-to-end deep conditional imitation learning for autonomous driving, Abdou, Mohammed, Kamal Hanan, El-Tantawy Samah, Abdelkhalek Ali, Adel Omar, Hamdy Karim, and Abaas Mustafa , 2019 31st International Conference on Microelectronics (ICM), p.346–350, (2019) Abstract
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Novel type-2 fuzzy logic technique for handover problems in a heterogeneous network, Saeed, Mohamed, Kamal Hanan, and El-Ghoneimy Mona , Engineering Optimization, Volume 50, Issue 9, p.1533-1543, (2018) Abstract

Small cells are deployed in the long-term evolution—advanced (LTE-A) data standard to satisfy rapidly increasing data rates at hotspots and enhance coverage in buildings. Small cells are low-cost, low-power nodes with limited coverage. With small cells, the more sophisticated network architecture increases the difficulty of dealing with mobility management. The conflict between traffic demands and network resources is also very important, and the signalling overhead (ping-pong) in the handover procedure should be considered in mobility management. With the aim of solving these issues, efficient handover algorithms are being used to enhance mobility management in small-cell networks. This article presents a new handover optimization algorithm for LTE-A networks based on fuzzy logic. It consists of selecting the optimum handover margins for both macro and small cells which are required for the handover

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