Search Results - (( early detection method algorithm ) OR ( parameter optimization method algorithm ))

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  1. 1

    Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm by Alyaa Ghazi Mohammed, Mohd Zakree Ahmad Nazri

    Published 2025
    “…In summary, this study advances the field by delivering an effective, optimized predictive algorithm for early heart disease detection, thereby offering valuable insights that could enhance healthcare outcomes, support proactive cardiovascular risk management, and pave the way for future innovations in personalized medicine…”
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    Article
  2. 2

    Early detection of dengue disease using extreme learning machine by Suhaeri, Suhaeri, Mohd Nawi, Nazri, Fathurahman, Muhamad

    Published 2018
    “…Therefore, the proposed ELM model can be considered as an alternative algorithm to apply for early detection of Dengue disease.…”
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    Article
  3. 3

    Hybridization of metaheuristic algorithm in training radial basis function with dynamic decay adjustment for condition monitoring / Chong Hue Yee by Chong , Hue Yee

    Published 2023
    “…As such, its training can reach stability in a shorter time compared to the gradient-descent based methods. To achieve optimal RBFN-DDA performance, HS (or GSA) is proposed to optimize the center and the width of each hidden unit in a trained RBFN. …”
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    Thesis
  4. 4

    Fair bandwidth distribution marking and scheduling algorithm in network traffic classification by Al-Kharasani, Ameen Mohammed Abdulkarem

    Published 2019
    “…Finally, propose a new method of obtaining optimal parameters dropping functions for Random Early Detection (RED) algorithm. …”
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    Thesis
  5. 5

    Color image enhancement of acute leukemia cells in blood microscopic image for leukemia detection sample by Harun, Nor Hazlyna, Abu Bakar, Juhaida, Abd Wahab, Zulkifli, Osman, Muhammad Khusairi, Harun, Hazaruddin

    Published 2020
    “…This report introduces a new enhancement method which is a combination of Particle swarm optimization (PSO) algorithm and contrast stretching, known as Hybrid PSO-Contrast stretching (HPSO-CS). …”
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    Conference or Workshop Item
  6. 6

    Vibration analysis for early detection of bearing failures by Gam, Kheng Shiang

    Published 2024
    “…The vibration monitoring algorithm utilizes time-domain parameters, frequency domain analysis, and envelope analysis to assess bearing conditions. …”
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    Final Year Project / Dissertation / Thesis
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  8. 8

    Training feedforward neural networks for fault diagnosis of ball bearing by Tuan Abdul Rahman, Tuan Ahmad Zahidi, As'arry, Azizan, Abdul Jalil, Nawal Aswan, Raja Ahmad, Raja Mohd Kamil

    Published 2018
    “…The results show that the proposed approach produces comparable classification accuracy as parameters of the FNNs were optimized systematically using CFS algorithm.…”
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    Conference or Workshop Item
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    Operational structural damage identification using de-noised modal feature in machine learning / Chen Shilei by Chen , Shilei

    Published 2021
    “…Meanwhile, the unsupervised learning method using PCA-WCC features is good at detecting unknown damage, and is sensitive to low-severity damage. …”
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    Thesis
  11. 11

    Optimisation of support vector machine hyperparameters using enhanced artificial bee colony variant to diagnose breast cancer by Ravindran, Nadarajan

    Published 2023
    “…Breast cancer is the leading cause of cancer-related deaths among women globally. Early detection through methods such as mammography and biopsy are crucial in reducing cancer-related mortality. …”
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    Thesis
  12. 12

    Evaluation of multiple In Situ and remote sensing system for early detection of Ganoderma boninense infected oil palm by Ahmadi, Seyedeh Parisa

    Published 2018
    “…In spite of the availability of tissue and DNA sampling techniques, there is a particular need for replacing costly field data collection methods for detecting Ganoderma in its early stage. …”
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    Thesis
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  14. 14

    Optimization of turning parameters using genetic algorithm method by Shah Izwandi, Mohd Zawawi

    Published 2008
    “…This study about development of optimization for turning parameters based on the Genetic Algorithm (GA). …”
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    Undergraduates Project Papers
  15. 15

    Early detection and mitigation of DDoS attacks in software defined networks by Al-Saadi, Mustafa Yahya Zakariya

    Published 2018
    “…The entropy increased and came close to the normal traffic entropy. The proposed method in this project was able to detect and mitigate the attack effectively in its early stages before the intensity escalate to a degree that exhausts the controller. …”
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    Thesis
  16. 16

    Parameters optimization of surface grinding process with particles swarm optimization, gravitational search, and sine cosine algorithms: a comparative analysis by Asrul, Adam

    Published 2018
    “…The efficiency of the three algorithms are evaluated and compared with previous results obtained by other optimization methods on similar studies. …”
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    Conference or Workshop Item
  17. 17

    Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization by Nur Iffah, Mohamed Azmi

    Published 2014
    “…Particle swarm optimization algorithm (PSO) is one of the artificial intelligence methods. …”
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    Thesis
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    Optimization of turning parameters using ant colony optimization by Mohamad Nazri, Semoin

    Published 2008
    “…The project objectives are to develop Ant Colony Optimization (ACO) algorithm for CNC turning process and to optimize turning parameters for minimized production cost per unit. …”
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    Undergraduates Project Papers
  20. 20

    Parameter estimation in double exponential smoothing using genetic algorithm / Foo Fong Yeng, Lau Gee Choon and Zuhaimy Ismail by Foo, Fong Yeng, Lau, Gee Choon, Ismail, Zuhaimy

    Published 2014
    “…Trial and error often serves as the best method to determine the parameter. Therefore, a good optimization technique is required for identify the best parameter in minimizing the forecast errors. …”
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    Research Reports