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  1. 1
    Optimized clustering with modified K-means algorithm

    Optimized clustering with modified K-means algorithm by Alibuhtto, Mohamed Cassim

    Published 2021
    “…Clustering technique is able to find hidden patterns and to extract useful information from huge data. Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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  2. 2
    The Determination of Pile Capacity Using Artificial Neural-net: An Optimization Approach

    The Determination of Pile Capacity Using Artificial Neural-net: An Optimization Approach by Ab. Malik, Rosely, Jamil S., Mohamed

    Published 2001
    “…Using the developed algorithm, the safety measures involved are such as reliability index and the probability of failure; instead of only factor of safety if conventional deterministic approach is used. …”
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  3. 3
    Iterative closed-loop identification of MIMO systems using ARX-based Leaky Least Mean Square Algorithm

    Iterative closed-loop identification of MIMO systems using ARX-based Leaky Least Mean Square Algorithm by Rahim, M.A., Ramasamy, M., Tufa, L.D., Faisal, A.

    Published 2014
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  4. 4
    Comparison of performance and computational complexity of nonlinear active noise control algorithms

    Comparison of performance and computational complexity of nonlinear active noise control algorithms by Sahib, Mouayad A., Raja Ahmad, Raja Mohd Kamil

    Published 2011
    “…The simulation results also suggest that it is more advantageous to use FXLMS for practical implementation of NANC.…”
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  5. 5
    MOTION PLANNING ALGORITHM FOR VEHICLE PARKING SIMULATION

    MOTION PLANNING ALGORITHM FOR VEHICLE PARKING SIMULATION by Mohd Hilmi, Amirul Ehsan

    Published 2008
    “…This project focuses on creation of the motion planning algorithm of the system and developing a simulation to simulate the vehicle movements. …”
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  6. 6
    Simulation of LMS algorithm for active noise cancellation / Ahmad Khairul Hafiz Abdullah

    Simulation of LMS algorithm for active noise cancellation / Ahmad Khairul Hafiz Abdullah by Abdullah, Ahmad Khairul Hafiz

    Published 2012
    “…MATLAB simulation will be used to simulate the adaptive filter to provide silent noise waveform. …”
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  7. 7
    Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm

    Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm by Manoharan P., Ravichandran S., Kavitha S., Tengku Hashim T.J., Alsoud A.R., Sin T.C.

    Published 2025
    “…The orthogonal learning mechanism improves the performance of the original GOOSE algorithm. This FC model uses the root mean squared error as the objective function for optimizing the unknown parameters. …”
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  8. 8
    Simulation model algorithm for pre-hospital emergency care (PHEC) volunteers in Indonesia

    Simulation model algorithm for pre-hospital emergency care (PHEC) volunteers in Indonesia by Martono, Martono, Sudiro, Sudiro, Satino, Satino

    Published 2018
    “…The statistic test used in this research is t-test. The results reveals that simulation model using algorithm influences the improvement of traffic volunteers’ emergency management capabilities with p-value of < 0.05 and mean score difference of 34.5%, and the model is highly effective to be implemented to improve the capability of traffic assistant volunteers to manage trauma emergency with the mean score difference of 11.5%. …”
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  9. 9
    IMPLEMENTATION OF NOISE CANCELLATION WITH HARDWARE DESCRIPTION LANGUAGE

    IMPLEMENTATION OF NOISE CANCELLATION WITH HARDWARE DESCRIPTION LANGUAGE by SUN, LEE KUANG

    Published 2006
    “…The objective of this project is to implement noise cancellation technique on an FPGA using Hardware Description Language. The performance of several adaptive algorithms is compared to determine the desirable algorithm used for adaptive noise cancellation system. …”
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  10. 10
    Checkpointing in selected most fitted resource task scheduling in grid computing

    Checkpointing in selected most fitted resource task scheduling in grid computing by Latip, Rohaya, Lew, Wai San, Chanchary, Fara Habib

    Published 2012
    “…The MeanFailureCP-SMF is simulated using Gridsim with initial checkpointing interval at 20% job execution time. …”
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  11. 11
    Simulation of LMS algorithm for active noise cancellation: article / Ahmad Khairul Hafiz Abdullah

    Simulation of LMS algorithm for active noise cancellation: article / Ahmad Khairul Hafiz Abdullah by Abdullah, Ahmad Khairul Hafiz

    Published 2012
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  12. 12
    Modified compound smoother in median algorithm of span size 42 / Nurul Nisa’ Khairol Azmi, Mohd Bakri Adam and Norhaslinda Ali

    Modified compound smoother in median algorithm of span size 42 / Nurul Nisa’ Khairol Azmi, Mohd Bakri Adam and Norhaslinda Ali by Khairol Azmi, Nurul Nisa’, Adam, Mohd Bakri, Ali, Norhaslinda

    Published 2019
    “…Median smoother of even window size is obtained by averaging the two middle points of arranged sequence using arithmetic mean. Some adjustments were proposed by substituting the algorithm of arithmetic mean using quadratic, geometric, harmonic and contraharmonic mean. …”
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  13. 13
    Simulation of shortest path using a-star algorithm / Nurul Hani Nortaja

    Simulation of shortest path using a-star algorithm / Nurul Hani Nortaja by Nurul Hani , Nortaja

    Published 2004
    “…The steps to calculate a shortest path using A • algorithm is shown by using appropriate examples and related figures. …”
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  14. 14
    Fuzzy C-Mean And Genetic Algorithms Based Scheduling For Independent Jobs In Computational Grid

    Fuzzy C-Mean And Genetic Algorithms Based Scheduling For Independent Jobs In Computational Grid by Lorpunmanee, Siriluck, Md Sap, Mohd Noor, Abdullah, Abdul Hanan

    Published 2006
    “…In this paper, we combine Fuzzy C-Mean and Genetic Algorithms which are popular algorithms, the Grid can be used for scheduling. …”
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  15. 15
    Extended multiple models selection algorithms based on iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm

    Extended multiple models selection algorithms based on iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm by Nur Azulia, Kamarudin

    Published 2019
    “…Simulation and empirical studies are conducted in validating the performance of the two algorithms. …”
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  16. 16
    Implementation of DSP-based optimal fuzzy logic speed controller for IM drive using quantum lightning search algorithm

    Implementation of DSP-based optimal fuzzy logic speed controller for IM drive using quantum lightning search algorithm by Abd. Ali J., Hannan M.A., Mohamed A., Pin Jern K., Abdolrasol M.G.

    Published 2023
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  17. 17
    Studying the Effect of Training Levenberg Marquardt Neural Network by Using Hybrid Meta-Heuristic Algorithms

    Studying the Effect of Training Levenberg Marquardt Neural Network by Using Hybrid Meta-Heuristic Algorithms by Abubakar, A., Khan, A., Nawi, N.M., Rehman, M.Z., Teh, Y.W., Chiroma, H., Herawan, T.

    Published 2016
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  18. 18
    Modeling and Analysis of New Hybrid Clustering Technique for Vehicular Ad Hoc Network

    Modeling and Analysis of New Hybrid Clustering Technique for Vehicular Ad Hoc Network by Abdulrazzak H.N., Hock G.C., Mohamed Radzi N.A., Tan N.M.L., Kwong C.F.

    Published 2023
    “…The effectiveness of the clustering model is the most important challenge. The K-Means clustering algorithm is an effective algorithm for multi-clusters that can be used in VANETs. …”
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  19. 19
    Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources

    Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources by Kumar, A., Ridha, S., Narahari, M., Ilyas, S.U.

    Published 2021
    “…In this research, a novel algorithm (Herschel Bulkley Network) is introduced to simulate the non-Newtonian fluid flow in a pipe using data redundant deep neural network (DNN) for fully developed, laminar, and incompressible flow conditions. …”
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  20. 20
    Studying the effect of training Levenberg Marquardt neural network by using hybrid meta-heuristic algorithms

    Studying the effect of training Levenberg Marquardt neural network by using hybrid meta-heuristic algorithms by Abubakar, Adamu, Khan, Abdullah, Nawi, Nazri Mohd, Rehman, M. Z., Teh , Ying Wah, Chiroma , Haruna, Herawan, Tutut

    Published 2016
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