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  1. 1
    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection

    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

    Published 2022
    “…The simulation is implemented with iFogSim and java programming language. …”
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  2. 2
    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing

    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

    Published 2011
    “…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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  3. 3
    Ant colony optimization algorithm for load balancing in grid computing

    Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2012
    “…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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  4. 4
    Hybrid meta-heuristic algorithm for solving multi-objective aggregate production planning in fuzzy environment

    Hybrid meta-heuristic algorithm for solving multi-objective aggregate production planning in fuzzy environment by Kalaf, Kalaf, Bayda Atiya

    Published 2017
    “…During the course of the present work, two fuzzy methods (modified Zimmermanns approach and modified angelovs approach ) and fourmeta-heuristics and hybrid meta heuristics including; simulated annealing (SA), modified simulated annealing (MSA), hybrid modified simulated annealing and simplex downhill (MSASD), hybrid modified simulated annealing and modified particle swarm optimization (MSAPSO) were proposed. …”
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  5. 5
    A modified Otsu’s algorithm for improving the performance of the energy detector in cognitive radio

    A modified Otsu’s algorithm for improving the performance of the energy detector in cognitive radio by Onumanyi, A. J., Onwuka, Elizabeth Nonye, Aibinu, Abiodun Musa, Ugweje, Okechukwu C., Salami, Momoh Jimoh Eyiomika

    Published 2017
    “…The modified algorithm was tested extensively and compared with other known algorithms using both simulated and real datasets. …”
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  6. 6
    OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT

    OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT by Murad S.S., Badeel R., Alsandi N.S.A., Alshaaya R.F., Ahmed R.A., Muhammed A., Derahman M.

    Published 2023
    “…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”
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  7. 7
    Adapting the conventional packet scheduling algorithms for simultaneous support of 5G multimedia traffic mix

    Adapting the conventional packet scheduling algorithms for simultaneous support of 5G multimedia traffic mix by Mohamed Rasied, Thaahirah Shireen, Mohd Ramli, Huda Adibah, Abdul Rahman, Farah Diyana, Najeeb, Athaur Rahman

    Published 2023
    “…The efficiency of the Modified Maximum-Largest Weighted Delay First (M-MLWDF) algorithm was demonstrated via computer simulation where the algorithm supports 112.9% more users over Modified Max-Rate (M-Max-Rate) and Modified Round Robin (M-RR) at the uRLLC QoS targets whilst meeting the target eMBB throughput.…”
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  8. 8
    A modified Otsu's algorithm for improving the performance of the energy detector in cognitive radio

    A modified Otsu's algorithm for improving the performance of the energy detector in cognitive radio by Onumanyi, A. J., Onwuka, Elizabeth Nonye, Aibinu, Abiodun Musa, Ugweje, Okechukwu C., Salami, Momoh Jimoh Eyiomika

    Published 2017
    “…The modified algorithm was tested extensively and compared with other known algorithms using both simulated and real datasets. …”
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  9. 9
    Enhanced path planning for industrial robot: integrating modified artificial potential field and A* algorithm / Fan Rui ... [et al.]

    Enhanced path planning for industrial robot: integrating modified artificial potential field and A* algorithm / Fan Rui ... [et al.] by -, Fan Rui, Ayub, Muhammad Azmi, Ab Patar, Mohd Nor Azmi, Che Abdullah, Sukarnur, Ahmat Ruslan, Fazlina

    Published 2024
    “…The study proposes a modified Artificial Potential Field (APF) method integrated with the A* algorithm to enhance industrial robot path planning for obstacle avoidance. …”
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  10. 10
    An FPGA implementation of exp-bet scheduling algorithm in LTE networks / Yusmardiah Yusuf

    An FPGA implementation of exp-bet scheduling algorithm in LTE networks / Yusmardiah Yusuf by Yusuf, Yusmardiah

    Published 2017
    “…For instance, various scheduling algorithms which offer several techniques in handling resources to the users have been developed such as Modified Largest Weighted Delay First (MLWDF), Proportional Fairness (PF) and Maximum Rate. …”
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  11. 11
    Enhanced convergence of Bat Algorithm based on dimensional and inertia weight factor

    Enhanced convergence of Bat Algorithm based on dimensional and inertia weight factor by Ramli, Mohamad Raziff, Abal Abas, Zuraida, Desa, Mohammad Ishak, Zainal Abidin, Zaheera, Al Azzam, Malik Bader Hasan

    Published 2019
    “…Thus, the phenomenon of slow convergence rate and low accuracy still exits. This paper aims to modify the exploitation of Bat Algorithm in optimising the solution by modifying dimensional size and providing inertia weight. …”
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  12. 12
    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization

    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

    Published 2019
    “…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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  13. 13
    Features selection for intrusion detection system using hybridize PSO-SVM

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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  14. 14
    Modified least trimmed squares method for face recognition / Nur Azimah Abdul Rahim

    Modified least trimmed squares method for face recognition / Nur Azimah Abdul Rahim by Abdul Rahim, Nur Azimah

    Published 2018
    “…It can be concluded that the modified algorithm decreases the biases, the variances and the mean squared errors of the LTS estimators. …”
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  15. 15
    Electroencephalography Simulation Hardware for Realistic Seizure, Preseizure and Normal Mode Signal Generation

    Electroencephalography Simulation Hardware for Realistic Seizure, Preseizure and Normal Mode Signal Generation by Mohamed, Shakir, Qidwai, Uvais, Malik, Aamir Saeed, Kamel , Nidal

    Published 2015
    “…The proposed hardware simulator will enhance researchers and hardware validators to simulate, validate and test their detection algorithms forehand, as well as for clinicians to use this system for training as well as for academic exercises. …”
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  16. 16
    Resource management in grid computing using ant colony optimization

    Resource management in grid computing using ant colony optimization by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2011
    “…Resources with high pheromone value are selected to process the submitted jobs.Global pheromone update is performed after completion processing the jobs in order to reduce the pheromone value of resources.A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against other ant based algorithm, in terms of resource utilization.Experimental results show that EACO produced better grid resource management solution.…”
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  17. 17
    Accelerating learning performance of back propagation algorithm by using adaptive gain together with adaptive momentum and adaptive learning rate on classification problems

    Accelerating learning performance of back propagation algorithm by using adaptive gain together with adaptive momentum and adaptive learning rate on classification problems by Abdul Hamid, Norhamreeza, Mohd Nawi, Nazri, Ghazali, Rozaida, Mohd Salleh, Mohd Najib

    Published 2011
    “…By computer simulations, we demonstrate that the proposed algorithm can give a better convergence rate and can find a good solution in early time compare to the conventional back propagation. …”
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  18. 18
    The effect of adaptive parameters on the performance of back propagation

    The effect of adaptive parameters on the performance of back propagation by Abdul Hamid, Norhamreeza

    Published 2012
    “…Thus, this research proposed a new method known as Back Propagation Gradient Descent with Adaptive Gain, Adaptive Momentum and Adaptive Learning Rate (BPGD-AGAMAL) which modifies the existing Back Propagation Gradient Descent algorithm by adaptively changing the gain, momentum coefficient and learning rate. …”
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  19. 19
    Modified Particle Swarm Optimization with Time Varying Acceleration Coefficients for Economic Load Dispatch with Generator Constraints

    Modified Particle Swarm Optimization with Time Varying Acceleration Coefficients for Economic Load Dispatch with Generator Constraints by Abdullah, M.N., Bakar, Ab Halim Abu, Rahim, N.A., Mokhlis, Hazlie, Illias, Hazlee Azil, Jamian, J.J.

    Published 2014
    “…The effectiveness of MPSO-TVAC algorithm is tested on different power systems with POZ, ramp-rate limits and transmission loss constraints. …”
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  20. 20
    Resource allocation technique for powerline network using a modified shuffled frog-leaping algorithm

    Resource allocation technique for powerline network using a modified shuffled frog-leaping algorithm by Altrad, Abdallah Mahmoud Mousa

    Published 2018
    “…The solution is numerically validated and verified by simulation-based powerline channel. The system performance was compared to similar research works in terms of the system’s capacity, scalability, allocated rate/power, and convergence. …”
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