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  1. 1
    Parallel implementation on improved error signal of backpropagation algorithm

    Parallel implementation on improved error signal of backpropagation algorithm by Mohd Aris, Teh Noranis

    Published 2001
    “…The experiments are implemented using the Sequent Symmetry SE30 parallel machine. …”
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  2. 2
    PID Parameters Improvement for AGC in Three Parallel-Connected Power Systems

    PID Parameters Improvement for AGC in Three Parallel-Connected Power Systems by Mushtaq, Najeeb, Ramdan, Razali, K. G., Mohammed, Hamdan, Daniyal, Ali, M. Humada

    Published 2016
    “…Integral Square Error (ISE) is considered as an objective function for both algorithms to determine its performance index value for the same parallel-connected power system. …”
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  3. 3
    Parallel execution of diagonally implicit Runge-Kutta methods for solving IVPs.

    Parallel execution of diagonally implicit Runge-Kutta methods for solving IVPs. by Ismail, Fudziah, Siri, Zailan, Othman, Mohamad, Suleiman, Mohamed

    Published 2009
    “…In this paper we used DIRK methods which are specifically designed for parallel execution to solve a set of initial value problems. …”
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  4. 4
    Parallel block methods for solving higher order ordinary differential equations directly

    Parallel block methods for solving higher order ordinary differential equations directly by Omar, Zurni

    Published 1999
    “…A new parallel algorithm for solving systems of ODEs using variable step size and order is also developed. …”
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  5. 5
    Voting algorithms for large scale fault-tolerant systems

    Voting algorithms for large scale fault-tolerant systems by Karimi, Abbas

    Published 2011
    “…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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  6. 6
    Parallel Kalman filter-based multi-human tracking in surveillance video

    Parallel Kalman filter-based multi-human tracking in surveillance video by Yussiff, A.-L., Yong, S.-P., Baharudin, B.B.

    Published 2014
    “…A Kalman filter is a recursive algorithm which predict the state variables and further uses the observed data to correct the predicted value. …”
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  7. 7
    Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm

    Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S., Al-Jumaily A.

    Published 2025
    “…After classifying the time set using the canopy with the K-means algorithm and the vector representation weighted by factors, the clustering impact is assessed using purity, precision, recall, and F value. …”
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  8. 8
    Application of intelligence based genetic algorithm for job sequencing problem on parallel mixed-model assembly line

    Application of intelligence based genetic algorithm for job sequencing problem on parallel mixed-model assembly line by Noroziroshan, Alireza, Mohd Ariffin, Mohd Khairol Anuar, Ismail, Napsiah

    Published 2010
    “…As the total objective values in most of problems could not be improved by simulated algorithm, it proved the well performing of proposed intelligence based genetic algorithm in reaching the near optimal solutions.…”
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  9. 9
    Parallel Block Methods for Solving Ordinary Differential Equations

    Parallel Block Methods for Solving Ordinary Differential Equations by Abdul Majid, Zanariah

    Published 2004
    “…The new codes were then used for the parallel implementation in solving large systems of first and higher order ODEs. …”
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  10. 10
    A Parallel-Model Speech Emotion Recognition Network Based on Feature Clustering

    A Parallel-Model Speech Emotion Recognition Network Based on Feature Clustering by Li-Min Zhang, Giap Weng Ng, Yu-Beng Leau, Hao Yan

    Published 2023
    “…We first extracted the emotion features from speech and calculated the F-Emotion value for each feature. These values were then used to determine the combination of speech emotion features that was optimal for speech emotion recognition. …”
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  11. 11
    A parallel-model speech emotion recognition network based on feature clustering

    A parallel-model speech emotion recognition network based on feature clustering by Li-Min Zhang, Giap Weng Ng, Yu-Beng Leau, Hao Yan

    Published 2023
    “…We first extracted the emotion features from speech and calculated the F-Emotion value for each feature. These values were then used to determine the combination of speech emotion features that was optimal for speech emotion recognition. …”
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  12. 12
    Parallel visualization approach of a 3D heart model

    Parallel visualization approach of a 3D heart model by Malekpour, A., Ling, T.C., Lim, W.C.

    Published 2008
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  13. 13
    Implementation of Parallel K-Means Algorithm to Estimate Adhesion Failure in Warm Mix Asphalt

    Implementation of Parallel K-Means Algorithm to Estimate Adhesion Failure in Warm Mix Asphalt by Akhtar, M.N., Ahmed, W., Kakar, M.R., Bakar, E.A., Othman, A.R., Bueno, M.

    Published 2020
    “…The results showed that the PKIP algorithm decreases the execution time up to 30 to 46 if compared with the sequential k means algorithm when implemented using multiprocessing and distributed computing. …”
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  14. 14
    Solving ordinary differential equations using block multistep method

    Solving ordinary differential equations using block multistep method by Mehrkanoon, Siamak

    Published 2011
    “…An eficient code based on block multistep method is developed for solving first and higher order initial value problems (IVPs) of ordinary differential equations (ODEs) using variable step size strategy. …”
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  15. 15
    Fpga Implementation Of Metaheuristic Optimization Algorithm

    Fpga Implementation Of Metaheuristic Optimization Algorithm by Phuah, Soon Eu

    Published 2022
    “…The selected metaheuristic was the Simulated Kalman Filter (SKF) which proposed an algorithm that was low in complexity and used a small number of steps. …”
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  16. 16
    FPGA implementation of metaheuristic optimization algorithm

    FPGA implementation of metaheuristic optimization algorithm by Nurul Hazlina, Noordin, Phuah, Soon Eu, Zuwairie, Ibrahim

    Published 2023
    “…The selected metaheuristic was the Simulated Kalman Filter (SKF) which proposed an algorithm that was low in complexity and used a small number of steps. …”
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  17. 17
    Partitioning techniques and their parallelization for stiff system of ordinary differential equations

    Partitioning techniques and their parallelization for stiff system of ordinary differential equations by Othman, Khairil Iskandar

    Published 2007
    “…Parallelizing the right algorithm in the partitioning code will give a better perfonnance with shorter execution times. …”
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  18. 18
    OPTIMIZATION OF HYBRID-FUZZY CONTROLLER FOR SERVOMOTOR CONTROL USING A MODIFIED GENETIC ALGORITHM

    OPTIMIZATION OF HYBRID-FUZZY CONTROLLER FOR SERVOMOTOR CONTROL USING A MODIFIED GENETIC ALGORITHM by WAHYUNGGORO, OYAS WAHYUNGGORO

    Published 2011
    “…The best controller is then selected to be optimized using SPOGA. Next, the performance comparison of GA and SPOGA is conducted based on the maximum value of parallel functions obtained. …”
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  19. 19
    Intelligent classification algorithms in enhancing the performance of support vector machine

    Intelligent classification algorithms in enhancing the performance of support vector machine by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2019
    “…Eight benchmark datasets from UCI were used in the experiments to validate the performance of the proposed algorithms. …”
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  20. 20
    Drone Based Image Processing For Precision Agriculture

    Drone Based Image Processing For Precision Agriculture by Sharif, Muhammad Arif Syafiq Md

    Published 2019
    “…At first, the parallel K-means clustering algorithm was applied on the acquired image to segregate various components acquired using UAV. …”
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