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  1. 1
    Genetic ensemble biased ARTMAP method of ECG-Based emotion classification

    Genetic ensemble biased ARTMAP method of ECG-Based emotion classification by Loo, C.K., Liew, W.S., Sayeed, M.S.

    Published 2012
    “…The proposed system utilizes Biased ARTMAP for pattern learning and classification. …”
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  2. 2
    Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals

    Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals by Too, Jing Wei

    Published 2020
    “…Therefore, this thesis aims to solve the feature selection problem in EMG signals classification and improve the classification performance of EMG pattern recognition system. …”
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  3. 3
    Differential evolution for neural networks learning enhancement

    Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

    Published 2008
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  4. 4
    Feature selection optimization using hybrid relief-f with self-adaptive differential evolution

    Feature selection optimization using hybrid relief-f with self-adaptive differential evolution by Zainudin, Muhammad Noorazlan Shah, Sulaiman, Md. Nasir, Mustapha, Norwati, Perumal, Thinagaran, Ahmad Nazri, Azree Shahrel, Mohamed, Raihani, Abd Manaf, Syaifulnizam

    Published 2017
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  5. 5
    Analysis on target detection and classification in LTE based passive forward scattering radar

    Analysis on target detection and classification in LTE based passive forward scattering radar by Raja Abdullah, Raja Syamsul Azmir, Abdul Aziz, Noor Hafizah, Abdul Rashid, Nur Emileen, Salah, Asem Ahmad, Hashim, Fazirulhisyam

    Published 2016
    “…The experimental results confirm the passive FSR system’s capability for ground target detection and classification. …”
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  6. 6
    Survival versus non-survival prediction after acute coronary syndrome in Malaysian population using machine learning technique / Nanyonga Aziida

    Survival versus non-survival prediction after acute coronary syndrome in Malaysian population using machine learning technique / Nanyonga Aziida by Nanyonga , Aziida

    Published 2019
    “…Prediction, identification, understanding and visualization of relationship between factors affecting mortality in ACS patients using feature selection and ML algorithms. …”
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  7. 7
    An improved method using fuzzy system based on hybrid boahs for phishing attack detection

    An improved method using fuzzy system based on hybrid boahs for phishing attack detection by Noor Syahirah, Nordin

    Published 2022
    “…The algorithms involved were Genetic Algorithm, Differential Evolution Algorithm, Particle Swarm Optimization, Butterfly Optimization Algorithm, Teaching-Learning-Based Optimization Algorithm, Harmony Search Algorithm and Gravitational Search Algorithm. …”
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  8. 8
    Improving Ant Swarm Optimization With Embedded Vaccination For Optimum Reducts Generation

    Improving Ant Swarm Optimization With Embedded Vaccination For Optimum Reducts Generation by Pratiwi, Lustiana, Choo, Yun Huoy, Draman @ Muda, Azah Kamilah, Draman @ Muda, Noor Azilah

    Published 2011
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  9. 9
    Fault tolerance structures in Wireless Sensor Networks (WSNs): survey, classification, and future directions

    Fault tolerance structures in Wireless Sensor Networks (WSNs): survey, classification, and future directions by Adday, Ghaihab Hassan, K. Subramaniam, Shamala, Ahmad Zukarnain, Zuriati, Samian, Normalia

    Published 2022
    “…Thus, the respective underlying Fault Tolerance (FT) structure is a critical requirement that needs to be considered when designing any algorithm in WSNs. Moreover, with the exponential evolution of IoT systems, substantial enhancements of current FT mechanisms will ensure that the system constantly provides high network reliability and integrity. …”
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  10. 10
    Deep learning detector for pests and plant disease recognition

    Deep learning detector for pests and plant disease recognition by Ileladewa, Oluwatimilehin Adekunle

    Published 2020
    “…And developing a quick and accurate model could help in detecting pests and diseases in plants. Meanwhile, evolution in deep convolutional neural networks for image classification has rapidly improved the accuracy of object detection, classification and system recognition. …”
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  11. 11
    Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm

    Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam, Sallehuddin, Roselina

    Published 2011
    “…Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning.…”
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  12. 12
    Predicting 30-day mortality after an acute coronary syndrome (ACS) using machine learning methods for feature selection, classification and visualization

    Predicting 30-day mortality after an acute coronary syndrome (ACS) using machine learning methods for feature selection, classification and visualization by Nanyonga Aziida, Sorayya Malek, Firdaus Aziz, Khairul Shafiq Ibrahim, Sazzli Kasim

    Published 2021
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  13. 13
    Classification of students' performance in computer programming course according to learning style

    Classification of students' performance in computer programming course according to learning style by Norwawi N.M., Abdusalam S.F., Hibadullah C.F., Shuaibu B.M.

    Published 2024
    Conference Paper
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  14. 14
    Classification of Students' Performance in Computer Programming Course According to Learning Style

    Classification of Students' Performance in Computer Programming Course According to Learning Style by Norwawi, NM, Abdusalam, SF, Hibadullah, CF, Shuaibu, BM

    Published 2024
    “…The findings show that that student's good performance in programming courses has a visual, active and sequential learning style.…”
    Proceedings Paper
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  15. 15
    Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level

    Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level by Hasan Mahmoud Sha'ban Kanaker

    Published 2024
    thesis::doctoral thesis
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  16. 16
    Class binarization with self-adaptive algorithm to improve human activity recognition

    Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

    Published 2018
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  17. 17
    Musical instrument identification using Convolutional Neural Network (CNN) algorithm / Muhammad Nur Azri Irfan Abdul Rahman

    Musical instrument identification using Convolutional Neural Network (CNN) algorithm / Muhammad Nur Azri Irfan Abdul Rahman by Abdul Rahman, Muhammad Nur Azri Irfan

    Published 2025
    “…This approach tried to overcome the limitations of the manual method and traditional algorithm, which tends to fail with the diverse dataset, diverse visual features, and scalability. …”
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  18. 18
    Enhancing understanding of programming concepts through physical games

    Enhancing understanding of programming concepts through physical games by Raja Yusof, Raja Jamilah, Habib, Ahsan

    Published 2017
    “…We produced in total 10 lesson games to illustrate variables, swapping, arrays, sorting algorithm particularly bubble sort, quicksort, selection sort, graph theory, dynamic programming, amortized analysis and trees. …”
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  19. 19
    Non-fungible token based smart manufacturing to scale Industry 4.0 by using augmented reality, deep learning and industrial Internet of Things

    Non-fungible token based smart manufacturing to scale Industry 4.0 by using augmented reality, deep learning and industrial Internet of Things by Ahmed Khan, Fazeel, Ibrahim, Adamu Abubakar

    Published 2023
    “…The next phase was deploying deep learning algorithms on a dataset having data generated from IIoT devices and sensors. …”
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  20. 20
    Extremal region detection and selection with fuzzy encoding for food recognition

    Extremal region detection and selection with fuzzy encoding for food recognition by Razali @ Ghazali, Mohd Norhisham

    Published 2019
    “…The second algorithm reduces the quantity of interest regions by using the Extremal Region Selection (ERS) algorithm. …”
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