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  1. 1
    Comparison of machine learning algorithms for estimating mangrove age using sentinel 2A at Pulau Tuba, Kedah, Malaysia / Fareena Faris Francis Singaram

    Comparison of machine learning algorithms for estimating mangrove age using sentinel 2A at Pulau Tuba, Kedah, Malaysia / Fareena Faris Francis Singaram by Faris Francis Singaram, Fareena

    Published 2021
    “…The supervised machine learning algorithm, SVM and Decision Tree are used for the estimation of the mangrove age into young and mature. …”
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  2. 2
    Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm

    Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm by Yap K.S., Abidin I.Z., Ahmad A.R., Hussien Z.F., Pok H.L., Ismail F.I., Mohamad A.M.

    Published 2023
    “…Genetic Algorithm (GA) is used to search for the best parameter of SVM classification by using combination of random and pre-populated genomes from Pre-Populated Database (PPD). …”
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  3. 3
    Interaction effect of process parameters and Pd-electrocatalyst in formic acid electro-oxidation for fuel cell applications: Implementing supervised machine learning algorithms

    Interaction effect of process parameters and Pd-electrocatalyst in formic acid electro-oxidation for fuel cell applications: Implementing supervised machine learning algorithms by Hossain S.K.S., Ali S.S., Rushd S., Ayodele B.V., Cheng C.K.

    Published 2023
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  4. 4
    A novel peak detection algorithm using particle swarm optimization for chew count estimation of a contactless chewing detection

    A novel peak detection algorithm using particle swarm optimization for chew count estimation of a contactless chewing detection by Selamat, Nur Asmiza, Md. Ali, Sawal Hamid, Minhad, Khairun Nisa’, Ahmad, Siti Anom, Sampe, Jahariah

    Published 2022
    “…The proposed chewing detection classifies the chewing activity with an overall accuracy of 96.4% using a medium Gaussian support vector machine (SVM). In accordance with the result, this article proposes a novel chew count estimation based on particle swarm optimization (PSO). …”
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  5. 5
    A novel peak detection algorithm using particle swarm optimization for chew count estimation of a contactless chewing detection

    A novel peak detection algorithm using particle swarm optimization for chew count estimation of a contactless chewing detection by Selamat, Nur Asmiza, Md. Ali, Sawal Hamid, Minhad, Khairun Nisa’, Ahmad, Siti Anom

    Published 2022
    “…The proposed chewing detection classifies the chewing activity with an overall accuracy of 96.4% using a medium Gaussian support vector machine (SVM). In accordance with the result, this article proposes a novel chew count estimation based on particle swarm optimization (PSO). …”
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  6. 6
    Direct approach for mining association rules from structured XML data

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
    “…The proposed method, XiFLEX has been implemented using two different techniques (java based & XQuery) and compared with the original FLEX algorithm in its basic implementation and the Apriori algorithm for frequent patterns generation. …”
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  7. 7
    Modeling the Nonlinearity of Sea Level Oscillations in the Malaysian Coastal Areas Using Machine Learning Algorithms

    Modeling the Nonlinearity of Sea Level Oscillations in the Malaysian Coastal Areas Using Machine Learning Algorithms by Lai V., Ahmed A.N., Malek M.A., Afan H.A., Ibrahim R.K., El-Shafie A., El-Shafie A.

    Published 2023
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  8. 8
    Machine learning methods for herschel-bulkley fluids in annulus: Pressure drop predictions and algorithm performance evaluation

    Machine learning methods for herschel-bulkley fluids in annulus: Pressure drop predictions and algorithm performance evaluation by Kumar, A., Ridha, S., Ganet, T., Vasant, P., Ilyas, S.U.

    Published 2020
    “…The impact of each input parameter affecting the pressure drop is quantified using the RF algorithm. …”
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  9. 9
    Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network

    Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network by Zafar, R., Kamel, N., Naufal, M., Malik, A.S., Dass, S.C., Ahmad, R.F., Abdullah, J.M., Reza, F.

    Published 2017
    “…MVPA-CNN based proposed algorithm is compared with region of interest (ROI) based method and MVPA based estimated values. …”
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  10. 10
    New techniques incorporating computational intelligence based for voltage stability evaluation and improvement in power system / Nur Fadilah Ab. Aziz

    New techniques incorporating computational intelligence based for voltage stability evaluation and improvement in power system / Nur Fadilah Ab. Aziz by Ab. Aziz, Nur Fadilah

    Published 2014
    “…Secondly, a new voltage stability prediction technique utilising state of the art machine learning, Support Vector Machine (SVM) was developed. At this stage, two popular SVM selection parameter methods, trial and error and cross validation were investigated and compared. …”
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  11. 11
    Optimization of COCOMO model using particle swarm optimization

    Optimization of COCOMO model using particle swarm optimization by Zakaria, Noor Azura, Ismail, Amelia Ritahani, Zainal Abidin, Nadzurah, Mohd Khalid, Nur Hidayah, Yakath Ali, Afrujaan

    Published 2021
    “…COnstructive COst MOdel (COCOMO) is a well-established software project estimation model; however, it lacks accuracy in effort and cost estimation, especially for current projects. …”
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  12. 12
    Image clustering comparison of two color segmentation techniques

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…There are many algorithm for analysing clustering each having its own method to do clustering. …”
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  13. 13
    Enhancing time series prediction with Hybrid AFSA-TCN: A unified approach to temporal data and optimization

    Enhancing time series prediction with Hybrid AFSA-TCN: A unified approach to temporal data and optimization by Nur Alia Shahira, Mohd Zaidi, Zuriani, Mustaffa, Muhammad Arif, Mohamad

    Published 2025
    “…The study introduces a hybrid model that integrates TCN with Artificial Fish Swarm Algorithm (AFSA), a bio-inspired optimization technique designed to fine-tune TCN parameters. …”
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  14. 14
    Mapreduce algorithm for weather dataset

    Mapreduce algorithm for weather dataset by Khalid Adam, Ismail Hammad

    Published 2017
    “…This original dataset is stored in Hadoop Distributed File System. Next, MapReduce Algorithm is developed using Java programming. The algorithm is tested using small and big dataset. …”
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  15. 15
    Novel approach for secure cover file of hidden data in the unused area within EXE file using computation between cryptography and steganography

    Novel approach for secure cover file of hidden data in the unused area within EXE file using computation between cryptography and steganography by Naji, Ahmed Wathik, Zaidan, B.B., Hameed, Shihab A., O-Khalifa, Othman

    Published 2009
    “…The strength of the information hiding science is due to the non-existence of standard algorithms to be used in hiding secret messages. Also there is randomness in hiding methods such as combining several media (covers) with different methods to pass a secret message. …”
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  16. 16
    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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  17. 17
    MapReduce algorithm for weather dataset

    MapReduce algorithm for weather dataset by Majid, Mazlina A., Romli, Awanis, Ahmad, Noraziah, Hammad, Khalid Adam Ismail

    Published 2018
    “…This original dataset is stored in Hadoop Distributed File System. Next, MapReduce Algorithm is developed using Java programming. The algorithm is tested using small and big dataset. …”
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  18. 18
    A comparative study of supervised machine learning approaches for slope failure production

    A comparative study of supervised machine learning approaches for slope failure production by Deris A.M., Solemon B., Omar R.C.

    Published 2023
    “…Current study applies two mostly used supervised machine learning approaches, support vector machine (SVM) and decision tree (DT) to predict the slope failure based on classification problem using historical cases. 148 of slope cases with six input parameters namely �unit weight, cohesion, internal friction angle, slope angle, slope height and pore pressure ratio and factor of safety (FOS) as an output parameter�, was collected from multinational dataset that has been extracted from the literature. …”
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  19. 19
    A malware analysis and detection system for mobile devices / Ali Feizollah

    A malware analysis and detection system for mobile devices / Ali Feizollah by Ali, Feizollah

    Published 2017
    “…Recent research has focused on analysing Android Intent in the XML file. We propose a new method of analysing Android Intent in Java code, which includes implicit intent and explicit intent. …”
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  20. 20
    Three-dimensional craniometrics identification model and cephalic index classification of Malaysian sub-adults: A multi-slice computed tomography study / Sharifah Nabilah Syed Mohd Hamdan

    Three-dimensional craniometrics identification model and cephalic index classification of Malaysian sub-adults: A multi-slice computed tomography study / Sharifah Nabilah Syed Mohd... by Sharifah Nabilah , Syed Mohd Hamdan

    Published 2024
    “…MIMICS software version 21.0 (Materialise, Leuven, Belgium) was used to construct 3D models and plane-to-plane (PTP) protocol was utilised to measure 14 selected craniometric parameters. Discriminant function analysis (DFA), binary logistic regression (BLR), and several machine learning (ML) algorithms (random forest (RF), support vector machines (SVM), and linear discriminant analysis (LDA)) were used to statistically analyse the data. …”
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