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Shuhaida Ismail
Shuhaida Ismail
Correu electrònic verificat a uthm.edu.my
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A hybrid model of self-organizing maps (SOM) and least square support vector machine (LSSVM) for time-series forecasting
S Ismail, A Shabri, R Samsudin
Expert Systems with Applications 38 (8), 10574-10578, 2011
1762011
Machine learning approach for flood risks prediction
N Razali, S Ismail, A Mustapha
IAES International Journal of Artificial Intelligence 9 (1), 73, 2020
492020
A hybrid model of self organizing maps and least square support vector machine for river flow forecasting
S Ismail, A Shabri, R Samsudin
Hydrology and Earth system sciences 16 (11), 4417-4433, 2012
442012
Behavioural features for mushroom classification
S Ismail, AR Zainal, A Mustapha
2018 IEEE symposium on computer applications & industrial electronics …, 2018
392018
A comparative study of different imputation methods for daily rainfall data in east-coast Peninsular Malaysia
SMCM Nor, SM Shaharudin, S Ismail, NH Zainuddin, ML Tan
Bulletin of Electrical Engineering and Informatics 9 (2), 635-643, 2020
212020
Time series forecasting using least square support vector machine for canadian lynx data
S Ismail, A Shabri
Jurnal Teknologi (Sciences & Engineering) 70 (5), 2014
212014
Predictive modelling of statistical downscaling based on hybrid machine learning model for daily rainfall in east-coast peninsular malaysia
NAF Sulaiman, SM Shaharudin, S Ismail, NH Zainuddin, ML Tan, ...
Symmetry 14 (5), 927, 2022
192022
River flow forecasting: a hybrid model of self organizing maps and least square support vector machine
S Ismail, R Samsudin, A Shabri
Hydrol Earth Syst Sci Discuss 7 (5), 8179-8212, 2010
152010
AI-powered COVID-19 forecasting: a comprehensive comparison of advanced deep learning methods
MU Tariq, SB Ismail
Osong Public Health and Research Perspectives 15 (2), 115, 2024
142024
Deep learning in public health: Comparative predictive models for COVID-19 case forecasting
MU Tariq, SB Ismail
Plos one 19 (3), e0294289, 2024
142024
Electricity consumption forecasting using adaptive neuro-fuzzy inference system (ANFIS)
KG Tay, H Muwafaq, WK Tiong, YY Choy
Univers. J. Electr. Electron. Eng 6, 37-48, 2019
132019
An efficient method to improve the clustering performance using hybrid robust principal component analysis-spectral biclustering in rainfall patterns identification
SM Shaharudin, S Ismail, SMCM Nor, N Ahmad
IAES International Journal of Artificial Intelligence 8 (3), 237, 2019
122019
Short-term forecasting of daily confirmed COVID-19 cases in Malaysia using RF-SSA model
SM Shaharudin, S Ismail, NA Hassan, ML Tan, NAF Sulaiman
Frontiers in public health 9, 604093, 2021
112021
Prediction of epidemic trends in COVID-19 with mann-kendall and recurrent forecasting-singular spectrum analysis
SM Shaharudin, S Ismail, MS Samsudin, A Azid, ML Tan, MAA Basri
Sains Malays 50 (4), 1131-1142, 2021
112021
Harnessing the power of AI: Advanced deep learning models optimization for accurate SARS-CoV-2 forecasting
MU Tariq, SB Ismail, M Babar, A Ahmad
PloS one 18 (7), e0287755, 2023
102023
Long short-term vs gated recurrent unit recurrent neural network for google stock price prediction
AN Sadon, S Ismail, NS Jafri, SM Shaharudin
2021 2nd International Conference on Artificial Intelligence and Data …, 2021
102021
Emerging trend of transaction and investment: bitcoin price prediction using machine learning
EC Loh, S Ismail
International Journal 9 (1.4), 2020
102020
Comparison of singular spectrum analysis forecasting algorithms for student’s academic performance during COVID-19 outbreak
MFM Fuad, SM Shaharudin, S Ismail, NAM Samsudin, MF Zulfikri
International Journal of Advanced Technology and Engineering Exploration 8 …, 2021
92021
Predictive modelling of covid-19 cases in Malaysia based on recurrent forecasting-singular spectrum analysis approach
SM Shaharudin, S Ismail, ML Tan, NS Mohamed, N AininaFilzaSulaiman
Int. J. Adv. Trends Comput. Sci. Eng 9, 2020
92020
Stream flow forecasting using principal component analysis and least square support vector machine
S Ismail, A Shabri
J. Appl. Sci. Agric 9, 170-180, 2014
92014
En aquests moments el sistema no pot dur a terme l'operació. Torneu-ho a provar més tard.
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