Search Results - a distribution ((((function algorithm) OR (selection algorithm))) OR (bat algorithm))

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  1. 1
    An improved bat algorithm with artificial neural networks for classification problems

    An improved bat algorithm with artificial neural networks for classification problems by Rehman Gillani, Syed Muhammad Zubair

    Published 2016
    “…Therefore, in order to improve the exploration and exploitation behavior of bats, this research proposed an improved Bat with Gaussian Distribution (BAGD) algorithm that takes small step lengths and ensures convergence to global optima. …”
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  2. 2
    Levy tunicate swarm algorithm for solving numerical and real-world optimization problems

    Levy tunicate swarm algorithm for solving numerical and real-world optimization problems by J. J., Jui, M. A., Ahmad, M. I. M., Rashid

    Published 2022
    “…The proposed Levy Tunicate Swarm Algorithm (LTSA) is a novel metaheuristic algorithm that integrates the Levy distribution into a new metaheuristic algorithm called Tunicate Swarm Algorithm (TSA) to solve numerical and real-world optimization problems. …”
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  3. 3
    Levy slime mould algorithm for solving numerical and engineering optimization problems

    Levy slime mould algorithm for solving numerical and engineering optimization problems by J. J., Jui, M. A., Ahmad, M. I. M., Rashid

    Published 2022
    “…The proposed Levy Slime Mould Algorithm (LSMA) is a novel metaheuristic algorithm that integrates the Levy distribution into a new metaheuristic called Slime Mould Algorithm (SMA) for solving numerical and engineering problems. …”
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  4. 4
    Network reconfiguration and control for loss reduction using genetic algorithm

    Network reconfiguration and control for loss reduction using genetic algorithm by Jawad, Mohamed Hassan Izzaldeen

    Published 2010
    “…In this work a feeder reconfiguration algorithm is presented for the purpose of power loss reduction in distribution networks. …”
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  5. 5
    Some metaheuristic algorithms for solving multiple cross-functional team selection problems

    Some metaheuristic algorithms for solving multiple cross-functional team selection problems by Ngo, S.T., Jaafar, J., Izzatdin, A.A., Tong, G.T., Bui, A.N.

    Published 2022
    “…We introduced a method that combines a compromise programming (CP) approach and metaheuristic algorithms, including the genetic algorithm (GA) and ant colony optimization (ACO), to solve the proposed optimization problem. …”
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  6. 6
    Enhanced Q-Learning algorithm for potential actions selection in automated graphical user interface testing

    Enhanced Q-Learning algorithm for potential actions selection in automated graphical user interface testing by Goh, Kwang Yi

    Published 2023
    “…We enhanced the Q-Learning algorithm for action selection based on potential action abilities and proposed a tool, namely CrashDroid, that allows the automation of testing context-aware Android applications. …”
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  7. 7
    Multi-objective Binary Clonal Selection Algorithm In The Retrieval Phase Of Discrete Hopfield Neural Network With Weighted Systematic Satisfiability

    Multi-objective Binary Clonal Selection Algorithm In The Retrieval Phase Of Discrete Hopfield Neural Network With Weighted Systematic Satisfiability by Romli, Nurul Atiqah

    Published 2024
    “…A Binary Clonal Selection Algorithm is being proposed to ensure optimal generation of the superior final neuron states. …”
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  8. 8
    Optimal network reconfiguration and intelligent service restoration prediction technique based on Cuckoo search spring algorithm / Mohamad Izwan Zainal

    Optimal network reconfiguration and intelligent service restoration prediction technique based on Cuckoo search spring algorithm / Mohamad Izwan Zainal by Zainal, Mohamad Izwan

    Published 2022
    “…In addition, objective function using the same CSSA algorithm were applied i.e., Vmin and Ploss as the objective function, and multi-objective involves Vmin and Ploss as the objective function. …”
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  9. 9
    Improving the exploration strategy of an automated android GUI testing tool based on the Q-Learning algorithm by selecting potential actions

    Improving the exploration strategy of an automated android GUI testing tool based on the Q-Learning algorithm by selecting potential actions by Goh, Kwang Yi, Baharom, Salmi, Din, Jamilah

    Published 2022
    “…It does not test most parts of a GUI within a reasonable amount of time and there is a high probability that the same actions are re-selected. …”
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  10. 10
    Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems

    Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems by Shakeel Ahmed, Kamboh

    Published 2014
    “…The DPA-EHD is further modified by utilizing the pipelining parallelism to reduce the computing iterations and named as data parallel and pipelining algorithm (DPPA-EHD). To implement the parallel algorithms a distributed parallel computing laboratory using easily available low cost computers is setup. …”
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  11. 11
    Streamflow prediction with large climate indices using several hybrid multilayer perceptrons and copula Bayesian model averaging

    Streamflow prediction with large climate indices using several hybrid multilayer perceptrons and copula Bayesian model averaging by Panahi F., Ehteram M., Ahmed A.N., Huang Y.F., Mosavi A., El-Shafie A.

    Published 2023
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  12. 12
    Fair bandwidth distribution marking and scheduling algorithm in network traffic classification

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

    Published 2019
    “…Second, propose an Optimized Time Sliding Window based Three Colour Marker. Finally, propose a new method of obtaining optimal parameters dropping functions for Random Early Detection (RED) algorithm. …”
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  13. 13
    DESIGN AND EVALUATION OF RESOURCE ALLOCATION AND JOB SCHEDULING ALGORITHMS ON COMPUTATIONAL GRIDS

    DESIGN AND EVALUATION OF RESOURCE ALLOCATION AND JOB SCHEDULING ALGORITHMS ON COMPUTATIONAL GRIDS by MEHMOOD SHAH, SYED NASIR

    Published 2012
    “…Experimental evaluation confirmed that the proposed grid scheduling algorithms possess a high degree of optimality in performance, efficiency and scalability.…”
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  14. 14
    Efficient genetic partitioning-around-medoid algorithm for clustering

    Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

    Published 2019
    “…This study utilizes genetic algorithms based upon the medoid rather than the mean as a centroid-selection schema to improve the clustering efficiency. …”
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  15. 15
    A Modified Particle Swarm Optimization for Efficient Maximum Power Point Tracking Under Partial Shading Condition

    A Modified Particle Swarm Optimization for Efficient Maximum Power Point Tracking Under Partial Shading Condition by Koh J.S., Tan R.H.G., Lim W.H., Tan N.M.L.

    Published 2024
    “…Extensive studies prove the proposed algorithm outperforms bat algorithm (BA), improved grey wolf optimizer (IGWO), conventional PSO and P&O, with convergence time shorter than 0.3 s and tracking accuracy above 99% under different complex PSCs. � 2010-2012 IEEE.…”
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  16. 16
    A Toolkit for Simulation of Desktop Grid Environment

    A Toolkit for Simulation of Desktop Grid Environment by FOROUSHAN, PAYAM CHINI

    Published 2014
    “…In this type of environment it is nearly impossible to prove the effectiveness of a scheduling algorithm. Hence the main objective of this study is to develop a desktop grid simulator toolkit for measuring and modeling scheduler algorithm performance. …”
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  17. 17
    Selection of access network using cost function method in heterogeneous wireless network

    Selection of access network using cost function method in heterogeneous wireless network by Mohamad Tahir, Hatim, Al-Ghushami, Abdullah Hussein, Yahya, Zainor Ridzuan

    Published 2014
    “…This method covers the weight distribution and cost factor techniques.The weight distribution is used to measure different weights for existing wireless network based on the user's preference and mobile terminal power.The cost factor technique is also used to identify the cost for performing handover target by considering every network parameters and its weight.Results obtained showed that the algorithm has the ability to increase user's satisfaction compared to other algorithms, which consistently choose one accessible network.…”
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  18. 18
    Probabilistic evaluation of wind power generation

    Probabilistic evaluation of wind power generation by Razali N.M.M., Misbah M.

    Published 2023
    “…The paper presents an algorithm developed for a random wind speed generator governed by the probability density function of Weibull distribution and evaluates the WTG's output by using the power curve of wind turbines. …”
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  19. 19
    PAPR Reduction Using Genetic Algorithm (GA) In OFDM System

    PAPR Reduction Using Genetic Algorithm (GA) In OFDM System by Mohd Ramdan, Fatin Najwa Nursyadza

    Published 2018
    “…GA is a type of optimization algorithm, which is natural-based selection and is used to find the optimal solution to the computational problem that maximizes or minimizes a particular function. …”
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  20. 20
    Improvement on optimal coordination of directional overcurrent relays in mesh distribution network system using artificial intelligence technique

    Improvement on optimal coordination of directional overcurrent relays in mesh distribution network system using artificial intelligence technique by Olufemi, Osaji Emmanuel

    Published 2015
    “…This research work propose the artificial intelligent (AI) solution on the conventional objective function (COF) and the modified objective function (MOF) formulation, with the application of genetic algorithm (GA) optimization solver, to determine each relay best optimal operation parameters selection for the time dial settings (TDS), plug setting (PS) and response time to fault accordingly. …”
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