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Ali N. Hasan
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Journal Articles
- 2024
- [j8]Mpho Sam Nkambule, Ali N. Hasan, Thokozani Shongwe:
Advanced Control Strategies for Photovoltaic Power Quality and Maximum Power Point Tracking Optimization. IEEE Access 12: 74456-74481 (2024) - 2023
- [j7]Babatunde S. Adejumobi, Thokozani Shongwe, Ali N. Hasan:
Improved Subcarrier Selection Technique for Power Line Communications. J. Commun. 18(2): 123-128 (2023) - 2022
- [j6]Katleho L. Masita, Ali N. Hasan, Thokozani Shongwe:
75MW AC PV Module Field Anomaly Detection Using Drone-Based IR Orthogonal Images With Res-CNN3 Detector. IEEE Access 10: 83711-83722 (2022) - 2021
- [j5]Ndamulelo Tshivhase, Ali N. Hasan, Thokozani Shongwe:
A Fault Level-Based System to Control Voltage and Enhance Power Factor Through an On-Load Tap Changer and Distributed Generators. IEEE Access 9: 34023-34039 (2021) - [j4]Ndamulelo Tshivhase, Ali N. Hasan, Thokozani Shongwe:
An Average Voltage Approach to Control Energy Storage Device and Tap Changing Transformers Under High Distributed Generation. IEEE Access 9: 108731-108753 (2021) - [j3]Babatunde S. Adejumobi, Thokozani Shongwe, Ali N. Hasan:
Mirror activation pattern selection techniques for media-based space-time block coded spatial modulation. Telecommun. Syst. 78(3): 307-316 (2021) - 2019
- [j2]Sibonelo Motepe, Ali N. Hasan, Riaan Stopforth:
Improving Load Forecasting Process for a Power Distribution Network Using Hybrid AI and Deep Learning Algorithms. IEEE Access 7: 82584-82598 (2019) - [j1]Sibonelo Motepe, Ali N. Hasan, Bhekisipho Twala, Riaan Stopforth:
Effective load forecasting for large power consuming industrial customers using long short-term memory recurrent neural networks. J. Intell. Fuzzy Syst. 37(6): 8219-8235 (2019)
Conference and Workshop Papers
- 2023
- [c16]Lukoki Mpova, Thokozani C. Shongwe, Ali N. Hasan:
The Classification and Detection of Cyanosis Images on Lightly and Darkly Pigmented Individual Human Skins Applying Simple CNN and Fine-Tuned VGG16 Models in TensorFlow's Keras API. CIVEMSA 2023: 1-6 - 2021
- [c15]Ali N. Hasan, Khawla M. Alhammadi:
Quality Monitoring of Abu Dhabi Drinking Water Using Machine Learning Classifiers. DeSE 2021: 1-6 - [c14]Katleho L. Masita, Ali N. Hasan, Thokozani Shongwe:
Refining the Efficiency of R-CNN in Pedestrian Detection. ICICT (3) 2021: 1-14 - [c13]Mpho Sam Nkambule, Ali N. Hasan, Ahmed Ali:
A Hybrid Model of Modified Robust Linear Regression Optimized by Ant Colony Optimization for Photovoltaic System Efficiency Improvement Under Sudden Change of Environmental Conditions. IECON 2021: 1-6 - [c12]E. M. Kuyunani, Ali N. Hasan, Thokozani Shongwe:
Improving voltage harmonics forecasting at a wind farm using deep learning techniques. ISIE 2021: 1-6 - 2020
- [c11]Dalal Baroud, Ali N. Hasan, Thokozani Shongwe:
A Study Towards Implementing Various Artificial Neural Networks for Signals Classification and Noise Detection in OFDM/PLC Channels. CSNDSP 2020: 1-6 - [c10]Dalal Baroud, Ali N. Hasan, Thokozani Shongwe:
The Use of Multiclass Support Vector Machines and Probabilistic Neural Networks for Signal Classification and Noise Detection in PLC/OFDM Channels. RADIOELEKTRONIKA 2020: 1-6 - 2018
- [c9]Katleho L. Masita, Ali N. Hasan, Satyakama Paul:
Pedestrian Detection Using R-CNN Object Detector. LA-CCI 2018: 1-6 - [c8]Satyakama Paul, Ali N. Hasan, Mario Bruno:
Exploring the non-linear relationship between various categories of Crimes and GDP: A case study using Generalized Additive Models. LA-CCI 2018: 1-5 - 2016
- [c7]Ali N. Hasan:
Evaluating the performance of single classifiers against multiclassifiers in monitoring underground dam levels and energy consumption for a deep gold mine pump station. IECON 2016: 907-911 - [c6]Ali N. Hasan, Thokozani Shongwe:
Proposed machine learning system to predict and estimate impulse noise in OFDM communication system. IECON 2016: 1016-1020 - [c5]Ali N. Hasan, Thokozani Shongwe:
Impulse Noise Detection in OFDM Communication System Using Machine Learning Ensemble Algorithms. SOCO-CISIS-ICEUTE 2016: 85-91 - 2015
- [c4]Ali N. Hasan, Bhekisipho Twala:
Improving single classifiers prediction accuracy for underground water pump station in a gold mine using ensemble techniques. EUROCON 2015: 1-7 - 2014
- [c3]Ali N. Hasan, Bhekisipho Twala, Tshilidzi Marwala:
Underground water dam levels and energy consumption prediction using computational intelligence techniques. CIVEMSA 2014: 94-99 - [c2]Ali N. Hasan, Bhekisipho Twala, Tshilidzi Marwala:
Moving towards accurate monitoring and prediction of gold mine underground dam levels. IJCNN 2014: 2844-2849 - 2013
- [c1]Ali N. Hasan, Bhekisipho Twala, Tshilidzi Marwala:
Predicting mine dam levels and energy consumption using artificial intelligence methods. CIES 2013: 171-175
Coauthor Index
aka: Thokozani C. Shongwe
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