A
Ali Najah Ahmed
Researcher at Universiti Tenaga Nasional
Publications - 210
Citations - 3937
Ali Najah Ahmed is an academic researcher from Universiti Tenaga Nasional. The author has contributed to research in topics: Computer science & Artificial neural network. The author has an hindex of 18, co-authored 137 publications receiving 1241 citations.
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Journal ArticleDOI
Machine learning methods for better water quality prediction
Ali Najah Ahmed,Faridah Othman,Haitham Abdulmohsin Afan,Rusul Khaleel Ibrahim,Chow Ming Fai,Shabbir Hossain,Mohammad Ehteram,Ahmed El-Shafie +7 more
TL;DR: A Neuro-Fuzzy Inference System (WDT-ANFIS) based augmented wavelet de-noising technique has been recommended that depends on historical data of the water quality parameter and exhibited a significant improvement in predicting accuracy for all theWater quality parameters and outperformed all the recommended models.
Journal ArticleDOI
Air quality status during 2020 Malaysia Movement Control Order (MCO) due to 2019 novel coronavirus (2019-nCoV) pandemic
Samsuri Abdullah,Amalina Abu Mansor,Nur Nazmi Liyana Mohd Napi,Wan Nurdiyana Wan Mansor,Ali Najah Ahmed,Marzuki Ismail,Zamzam Tuah Ahmad Ramly +6 more
TL;DR: It was found that the PM2.5 concentrations showed a high reduction during the 2020 Malaysia Movement Control Order, but the reduction did not solely depend on MCO, thus the researchers suggest a further study considering the influencing factors that need to be adhered to in the future.
Journal ArticleDOI
Improving artificial intelligence models accuracy for monthly streamflow forecasting using grey Wolf optimization (GWO) algorithm
TL;DR: The results show the integrated AI with GWO outperform the standard AI methods and can make better forecasting during training and testing phases for the monthly inflow in all input cases, revealing the superiority of GWO meta-heuristic algorithm in improving the accuracy of the standardAI in forecasting the monthly Inflow.
Journal ArticleDOI
Extreme gradient boosting (Xgboost) model to predict the groundwater levels in Selangor Malaysia
Ahmedbahaaaldin Ibrahem Ahmed Osman,Ali Najah Ahmed,Ming Fai Chow,Yuk Feng Huang,Ahmed El-Shafie,Ahmed El-Shafie +5 more
TL;DR: The proposed Xgboost model outperformed both the Artificial Neural Network and Support Vector Regression models for all different input combinations and serves as a great benchmark for future groundwater levels prediction using Xg Boost algorithm.
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Rainfall forecasting model using machine learning methods: Case study Terengganu, Malaysia
Wanie M. Ridwan,Michelle Sapitang,Awatif Aziz,Khairul Faizal Kushiar,Ali Najah Ahmed,Ahmed El-Shafie,Ahmed El-Shafie +6 more
TL;DR: In this article, a comparative study was conducted focusing on developing and comparing several Machine Learning (ML) models, evaluating different scenarios and time horizon, and forecasting rainfall using two types of methods.