Machine learning autoencoder‐based parameters prediction for solar power generation systems in smart grid A Zafar, Y Che, M Faheem, M Abubakar, S Ali, MS Bhutta IET Smart Grid, 2024 | 11 | 2024 |
Enhancing Power Generation Forecasting in Smart Grids using Hybrid Autoencoder Long Short-Term Memory Machine Learning Model. A Zafar, Y Che, M Ahmed, M Sarfraz, A Ahmad, M Alibakhshikenari IEEE Access, 2023 | 7 | 2023 |
Survey on driving behavior and motivational factors causing aggressive driving: A case study of Peshawar, Pakistan MU Farooq, MU Ghani, A Zafar Proceedings of the 2nd International Conference on Emerging Trends in …, 2016 | 4 | 2016 |
Improved Performance of Silicon-Germanium Solar Cell Based on Optimization of Layer Thickness N Shah, A Zafar City University International Journal of Computational Analysis 5 (1), 1-10, 2022 | 2 | 2022 |
Optimizing solar power generation forecasting in smart grids: a hybrid convolutional neural network-autoencoder long short-term memory approach A Zafar, Y Che, M Sehnan, U Afzal, AD Algarni, H Elmannai Physica Scripta 99 (9), 095249, 2024 | 1 | 2024 |
Atomistic DFT simulations are promising techniques for the discovery of hydrogen storage materials. AZ Bibi Zunaira, Mubashar Ali, Masood Yousaf Journal of Engineering, Science and Technological Trends 1 (2), 100-106, 2024 | | 2024 |
Improved Solar Power Prediction Using CNN-LSTM Models for Optimized Smart Grid Performance MA Ahsan Aamina, Ahsan Zafar, Muhammad Adeel Afzal, Mubashar Javed, Daniyal ... Journal of Engineering, Science and Technological Trends 1 (2), 87-99, 2024 | | 2024 |
Evaluation of Machine Learning Models for Predicting Smart Grid Parameters A Zafar, Y Che, S Rasool, U Afzal, A Aamina Proceedings of the 5th International Conference on Emerging Trends in …, 2023 | | 2023 |
OFFSHORE WIND ENERGY CONNECTED TO HVDC SYSTEM, VSC CONTROL A Zafar City University International Journal of Computational Analysis 3 (1), 29-40, 2019 | | 2019 |