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  1. 1
    Identifying Damage Types in Solar Panels Through Surface Image Analysis with Naive Bayes

    Identifying Damage Types in Solar Panels Through Surface Image Analysis with Naive Bayes by Wiliani, Ninuk, T.K.A, Rahman, Ramli, Suzaimah

    Published 2024
    “…Identifying and categorizing faults on solar panel surfaces is essential for maintenance, as these defects considerably affect energy output and system efficiency. …”
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  2. 2
    Lightning damage assessment on solar panels using in-house portable infrared thermography camera with Convolutional Neural Network (CNN) algorithm

    Lightning damage assessment on solar panels using in-house portable infrared thermography camera with Convolutional Neural Network (CNN) algorithm by Chandrasegaran, Ormiila, Mustapha, Faizal, Abdullah, Mohd Na’im, Anwar, Murniwati, Mustapha, Mazli, Adzis, Zuraimy

    Published 2024
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  3. 3
    Segmentation of MRI brain images using statistical approaches

    Segmentation of MRI brain images using statistical approaches by Balafar, Mohammad Ali

    Published 2011
    “…Also, a filter-based image inhomogeneity-correction algorithm is proposed which uses the maximum filter for inhomogeneity field estimation. …”
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  4. 4
    Improving Photometric Redshifts By Varying Activation Functions In Artificial Neural Networks

    Improving Photometric Redshifts By Varying Activation Functions In Artificial Neural Networks by Pathi, Imdad Binti Mahmud

    Published 2024
    “…The Artificial Neural Network Redshift (annz) algorithm is a fast and simple machine learning photometric redshift estimator. …”
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  5. 5
    Development of electronic nose for classification of aromatic herbs using Artificial Intelligent techniques

    Development of electronic nose for classification of aromatic herbs using Artificial Intelligent techniques by Che Soh, Azura, Mohamad Radzi, Nur Fadzilah, Mohamad Yusof, Umi Kalsom, Ishak, Asnor Juraiza, Hassan, Mohd Khair

    Published 2018
    “…Two classification methods, Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) were used in order to investigate the performance of classification accuracy for this E-nose system. …”
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  6. 6
    Kinetic parameters estimation of the Escherichia coli (E. coli) model by Garra Rufa-inspired Optimization Algorithm (GRO)

    Kinetic parameters estimation of the Escherichia coli (E. coli) model by Garra Rufa-inspired Optimization Algorithm (GRO) by Jasni, Mohamad Zain, Azrag, Mohammed Adam Kunna, Saiful Farik, Mat Yatin, Aldehim, Ghadah, Zuhaira, Muhammad Zain, Shaiba, Hadil, Alturki, Nazik, Sapiah, Sakri, Azlinah, Mohamed, Jaber, Aqeel S.

    Published 2024
    “…As a result of this new method, it was discovered that small-scale and even whole-cell dynamic models can be estimated accurately.…”
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  7. 7
    Robust estimation methods for fixed effect panel data model having block-concentrated outliers

    Robust estimation methods for fixed effect panel data model having block-concentrated outliers by Abu Bakar @ Harun, Nor Mazlina

    Published 2019
    “…The Ordinary Least Squares (OLS) is the commonly used method to estimate the parameters of fixed effect panel data model. …”
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  8. 8
    Scale-invariant and adaptive-search template matching for monocular visual odometry in low-textured environment

    Scale-invariant and adaptive-search template matching for monocular visual odometry in low-textured environment by Aqel, Mohammad O. A.

    Published 2016
    “…This method is one of the most effective methods for template matching. …”
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  9. 9
    Malaysia solar energy experience: intelligent fault location algorithm for unbalanced radial distribution network including PV systems

    Malaysia solar energy experience: intelligent fault location algorithm for unbalanced radial distribution network including PV systems by Farzan, Payam, Izadi, Mahdi, Gomes, Chandima, Hesamian, Mohammad Hesam

    Published 2016
    “…The recorded values are evaluated by a designed and tuned multi-layer feed forward neural network and the fault distances from the source are estimated accordingly. In order to highlight the accuracy of the presented method, the scenario is also repeated by recording the peak values of short circuit current which have been mostly used in the published intelligent fault location studies and the obtained results via two different values are compared with each other. …”
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  10. 10
    Robust variable selection methods for large- scale data in the presence of multicollinearity, autocorrelated errors and outliers

    Robust variable selection methods for large- scale data in the presence of multicollinearity, autocorrelated errors and outliers by Uraibi, Hassan S.

    Published 2016
    “…In this situation, the existing Elastic-Net and RE-Net methods are not capable of selecting the important variables in the final model. …”
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  11. 11
    Automated Scaling Region of Interest with Iterative Edge Preserving in Forward-Backward Time-Stepping

    Automated Scaling Region of Interest with Iterative Edge Preserving in Forward-Backward Time-Stepping by Juliana, Binti Nawawi

    Published 2019
    “…Average RE is 61.94% for a circular shape in breast model, meanwhile attains RE of 4.17% for a U-shape object. …”
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  12. 12
    Multi-objective optimization of stand-alone hybrid renewable energy system by genetic algorithm

    Multi-objective optimization of stand-alone hybrid renewable energy system by genetic algorithm by Nejad, Mohsen Fadaee

    Published 2013
    “…Among these methods, Genetic Algorithm and Particle Swarm Optimization are known as two most effective methods for HRESs. …”
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  13. 13
    Improved Boosted Decision Tree Algorithms by Adaptive Apriori and Post-Pruning for Predicting Obstructive Sleep Apnea

    Improved Boosted Decision Tree Algorithms by Adaptive Apriori and Post-Pruning for Predicting Obstructive Sleep Apnea by Sim, Doreen Ying Ying, Teh, Chee Siong, Ahmad Izuanuddin, Ismail

    Published 2018
    “…The novelty of the post-pruning technique applied is that it is augmented by AA properties and these depend on the data characteristics in the dataset(s) being accessed. This algorithm is then boosted by using AdaBoost ensemble method. …”
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  14. 14
    Defect Detection And Classification Of Silicon Solar Wafer Featuring Nir Imaging And Improved Niblack Segmentation

    Defect Detection And Classification Of Silicon Solar Wafer Featuring Nir Imaging And Improved Niblack Segmentation by Mahdavipour, Zeinab

    Published 2016
    “…In this thesis, an automatic and efficient defect detection system, utilising advanced classification and clustering strategies are proposed. …”
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  15. 15
    Robust Kernel Density Function Estimation

    Robust Kernel Density Function Estimation by Dadkhah, Kourosh

    Published 2010
    “…The classical kernel density estimation technique is the commonly used method to estimate the density function. …”
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  16. 16
    Retinal image blood vessel extraction and quantification with Euclidean distance transform approach

    Retinal image blood vessel extraction and quantification with Euclidean distance transform approach by Kuryati, Kipli, Mohammed Enamul, Hoque, Lik, Thai Lim, Tengku Mohd Afendi, Zulcaffle, Siti Kudnie, Sahari, Muhammad Hamdi, Mahmood

    Published 2020
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  17. 17
    Effect of corrugated wall combined with backward-facing step channel on fluid flow and heat transfer

    Effect of corrugated wall combined with backward-facing step channel on fluid flow and heat transfer by Hilo, Ali Kareem, Abu Talib, Abd Rahim, Iborra, Antonio Acosta, Hameed Sultan, Mohamed Thariq, Abdul Hamid, Mohd Faisal

    Published 2020
    “…The governing equation was solved using Finite Volume Method (FVM) and the SIMPLE algorithm was applied to investigate the effect of backward-facing step with corrugated downstream on heat transfer characteristics. …”
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  18. 18
    Intelligent algorithm based modeling of renewable and green energy resources for microgrid optimization

    Intelligent algorithm based modeling of renewable and green energy resources for microgrid optimization by Khamis, Alias

    Published 2025
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  19. 19
    State-of-charge estimation for lithium-ion batteries with optimized self-supervised transformer deep learning model

    State-of-charge estimation for lithium-ion batteries with optimized self-supervised transformer deep learning model by Dickson Neoh Tze How, Dr.

    Published 2023
    “…To select the optimal hyperparameters for the Transformer model, the Tree Parzen Estimator(TPE) optimization in combination with the Hyperband pruning algorithm is employed to search for the best combination that yields the lowest Root Mean Squared Error(RMSE)and Mean Absolute Error (MAE) error metrics. …”
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  20. 20
    Energy, Vibration And Sound Research Group (e-VIBS) School Of Science And Technology Universiti Malaysia Sabah : Bioacoustics Signal Modeling Using Time-Frequency Distribution

    Energy, Vibration And Sound Research Group (e-VIBS) School Of Science And Technology Universiti Malaysia Sabah : Bioacoustics Signal Modeling Using Time-Frequency Distribution by Jedol Dayou, Ng, Chee Han, Ho, Chong Mun, Abdul Hamid Ahmad, Mohd Noh Dalimin, Sithi V. Muniandy

    Published 2011
    “…However, WSE was the best method for the RE approach with the accuracy of 92%. …”
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