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  1. 1

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

    Published 2012
    “…This research proposes an enhancement of the ant colony optimization algorithm that caters for dynamic scheduling and load balancing in the grid computing system. …”
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    Monograph
  2. 2

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

    Published 2011
    “…This research proposes an Enhanced Ant Colony Optimization (EACO) algorithm that caters dynamic scheduling and load balancing in the grid computing system. …”
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    Thesis
  3. 3

    Water level forecasting using feed forward neural networks optimized by African Buffalo Algorithm (ABO) by Ahmed, Ehab Ali

    Published 2019
    “…This research proposed a swarm intelligence training algorithm, Improved African Buffalo Optimization algorithm (IABO) based on the Metaheuristic method called the African Buffalo Optimization algorithm (ABO). …”
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    Thesis
  4. 4

    Extending the decomposition algorithm for support vector machines training by Zaki, N,M., Deris, S., Chin, K.K.

    Published 2003
    “…The decomposition algorithm developed by Osuna et al. (1997a) reduces the training cost to an acceptable level. …”
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    Article
  5. 5

    PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM by ABDALLA, OSMAN AHMED

    Published 2011
    “…This research focuses on the use of binaryencoded genetic algorithm (GA) to implement efficient search strategies for the optimal architecture and training parameters of a multilayer feed-forward ANN. …”
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    Thesis
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    A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models by ul Islam, B., Baharudin, Z.

    Published 2017
    “…The results show that the neural network optimized with genetic algorithm and trained with an optimally and intelligently selected input vector containing historical load and meteorological variables produced the best prediction accuracy. …”
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    Article
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    Accelerated mine blast algorithm for ANFIS training for solving classification problems by Mohd Salleh, Mohd Najib, Hussain, Kashif

    Published 2016
    “…Mine Blast Algorithm (MBA) is newly developed metaheuristic technique. …”
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    Article
  10. 10

    Adapting and enhancing mussels wandering optimization algorithm for supervised training of neural networks by Abusnaina, Ahmed A. A.

    Published 2015
    “…In addition, training NN is still highly-time consuming. The Mussels Wandering Optimization (MWO) is a recent metaheuristic optimization algorithm inspired ecologically by mussels movement behavior. …”
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    Thesis
  11. 11

    Neural network modeling and optimization for spray-drying coconut milk using genetic algorithm and particle swarm optimization by Lee, Jesee Kar Ming

    Published 2022
    “…Firstly, using MATLAB program, the ANN model is developed based on optimized topology and is then furthered optimized by genetic algorithm (GA) and particle swarm optimization (PSO) using MINITAB program. …”
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    Thesis
  12. 12

    Autoreclosure in Extra High Voltage Lines using Taguchi’s Method and Optimized Neural Networks by Desta, Zahlay F., K.S., Ramarao, Taj, Mohammed Baloch

    Published 2008
    “…The developed algorithm is effectively trained, verified and validated with a set of training, dedicated testing and validation data respectively.…”
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    Conference or Workshop Item
  13. 13

    Autoreclosure in Extra High Voltage Lines using Taguchi's Method and Optimized Neural Networks by Desta, Zahlay F., K.S., Rama Rao

    Published 2009
    “…The developed algorithm is effectively trained, verified and validated with a set of training, dedicated testing and validation data respectively.…”
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    Conference or Workshop Item
  14. 14

    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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    Monograph
  15. 15

    Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin by Hussin, Noor Rasyidah

    Published 2014
    “…Bat algorithm was employed to optimize the training parameters such as learning rate, momentum rate and number of neurons in hidden layers. …”
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    Article
  16. 16

    Predicting attackers of online shaming using ant colony optimization / Noor Shafiqa Fazlien Mohamad Fauzi by Mohamad Fauzi, Noor Shafiqa Fazlien

    Published 2020
    “…This study implemented Ant Colony Optimization Algorithm to develop classification rules for predicting the attackers of online shaming. …”
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    Thesis
  17. 17

    Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter by Azhar, Nur Huwaina

    Published 2019
    “…Cloudsim is used as Discrete Event Simulation tool and Java as coding language to evaluate LACE algorithm. …”
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    Thesis
  18. 18

    Hybrid bat algorithm hybrid-artificial neural network for modeling operating photovoltaic module temperature / Noor Rasyidah Hussin by Hussin, Noor Rasyidah

    Published 2014
    “…Bat algorithm was employed to optimize the training parameters such as learning rate, momentum rate and number of neurons in hidden layers. …”
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    Thesis
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    Optimization of Prediction Error in CO2 Laser Cutting process by Taguchi Artificial Neural Network Hybrid with Genetic algorithm by Nukman, Y., Hassan, M.A., Harizam, M.Z.

    Published 2013
    “…In some cases, the prediction errors of Taguchi ANN model was larger than 10 even with Levenberg Marquardt training algorithm. To overcome such problem, a hybrid genetic algorithm-based Taguchi ANN (GA-Taguchi ANN) has been developed. …”
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    Article