Search Results - global contributing ((function algorithm) OR (selection algorithm))

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  1. 1
    Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh

    Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh by Rawaa Dawoud Hassan, Al-Dabbagh

    Published 2015
    “…The performance of DE algorithm depends heavily on the selected mutation strategy and its associated control parameters. …”
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  2. 2
    Chaos search in fourire amplitude sensitivity test

    Chaos search in fourire amplitude sensitivity test by Koda, Masato

    Published 2012
    “…Work in Artificial Intelligence (AI) often involves search algorithms. In many complicated problems, however, local search algorithms may fail to converge into global optimization and global search procedures are needed. …”
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  3. 3
    Chaos Search in Fourier Amplitude Sensitivity Test

    Chaos Search in Fourier Amplitude Sensitivity Test by Koda, Masato

    Published 2012
    “…Work in Artificial Intelligence (AI) often involves search algorithms. In many complicated problems, however, local search algorithms may fail to converge into global optimization and global search procedures are needed. …”
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  4. 4
    A comparative analysis of machine learning algorithms for diabetes prediction

    A comparative analysis of machine learning algorithms for diabetes prediction by Alansari, Waseem Abdulmahdi, Masnizah Mohd

    Published 2024
    “…The study contributes insights into the importance of pre-processing and feature selection in improving algorithm performance. …”
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  5. 5
    Enhanced multi-objective evolutionary mating algorithm with improved crowding distance and levy flight for optimizing comfort index and energy consumption in smart buildings

    Enhanced multi-objective evolutionary mating algorithm with improved crowding distance and levy flight for optimizing comfort index and energy consumption in smart buildings by Muhammad Naim, Nordin, Mohd Herwan, Sulaiman, Nor Farizan, Zakaria, Zuriani, Mustaffa

    Published 2025
    “…The proposed MOEMA enhances the original EMA framework through two key innovations: an improved crowding distance function inspired by the Non-dominated Sorting Genetic Algorithm (NSGA) to enhance solution diversity and selection pressure, and the integration of Levy flight mechanics to improve exploration efficiency by balancing local and global searches. …”
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  6. 6
    Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling

    Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling by Anuar, Nurul Izah

    Published 2022
    “…The discrete MOPSO also includes the modified maximin fitness function to promote solution diversity in the selection of global best solutions. …”
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  7. 7
    Optimization of Upstream Offshore Oilfield Production Planning under Uncertainty and Downstream Crude Oil Scheduling at Refinery Front-End

    Optimization of Upstream Offshore Oilfield Production Planning under Uncertainty and Downstream Crude Oil Scheduling at Refinery Front-End by Tan Yin Keong, Tan Yin

    Published 2012
    “…In order to obtain a global optimum solution of the problem, an outer-approximation algorithm is proposed, whereby lower and upper bounds on the global optimum are generated, which are converged to a specified tolerance. …”
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  8. 8
    Optimization of Upstream Offshore Oilfield Production Planning under Uncertainty and Downstream Crude Oil Scheduling at Refinery Front-End

    Optimization of Upstream Offshore Oilfield Production Planning under Uncertainty and Downstream Crude Oil Scheduling at Refinery Front-End by Tan , Yin Keong

    Published 2009
    “…In order to obtain a global optimum solution of the problem, an outer-approximation algorithm is proposed, whereby lower and upper bounds on the global optimum are generated, which are converged to a specified tolerance. …”
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  9. 9
    Discrete-time system identification using genetic algorithm with single parent-based mating technique

    Discrete-time system identification using genetic algorithm with single parent-based mating technique by Zainuddin, Farah Ayiesya

    Published 2024
    “…This research focuses on improving Genetic Algorithms (GA) for SI, specifically addressing inefficiencies in common crossover operators that limit search space exploration and lead to premature convergence. …”
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  10. 10
    A New And Fast Rival Genetic Algorithm For Feature Selection

    A New And Fast Rival Genetic Algorithm For Feature Selection by Too, Jing Wei, Abdullah, Abdul Rahim

    Published 2021
    “…Presently, many metaheuristic optimization algorithms were successfully applied for feature selection. …”
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  11. 11
    PSO-LFDE Algorithm on Constrained Real-Parameter Optimisation Test Functions

    PSO-LFDE Algorithm on Constrained Real-Parameter Optimisation Test Functions by Nafrizuan, Mat Yahya, Nur Iffah, Mohamed Azmi

    Published 2023
    “…The proposed algorithm will hold a better exploration–exploitation equilibrium if the contributions of convergence and diversity and global and individual bests in attracting particles are maintained in balance. …”
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  12. 12
    Optimization of photovoltaic energy harvesting using clonal selection algorithm

    Optimization of photovoltaic energy harvesting using clonal selection algorithm by Tan, Min Keng, Grace Butiza Joponi, Lim, Ahmad Razani Haron, Chai, Chang-Yii, Tze, Kenneth Kin Teo

    Published 2023
    “…To address this issue, the Clonal Selection Algorithm (CSA) is proposed as an effective approach to enhance MPPT algorithm performance. …”
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  13. 13
    Enhancing harmony search parameters based on step and linear function for bus driver scheduling and rostering problems

    Enhancing harmony search parameters based on step and linear function for bus driver scheduling and rostering problems by Mansor, Nur Farraliza

    Published 2018
    “…Therefore,it is of great interest that we find adjustments for these parameters in this research.There are two contributions to this research.The first one is having HMCR parameter using step function and the linear increase function while the second is applying the fret spacing concept on guitars that is associated with mathematical formulae is also applied in the BW parameter.There are three proposed models on the alteration of HMCR parameters based on the use of the fundamental step function;namely,the constant interval of step function, and its dynamic increase and decrease interval functions.The experimental results revealed that our proposed approach is superior to other state of the art harmony searches either in specific or generic cases. …”
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  14. 14
    An empirical study of density and distribution functions for ant swarm optimized rough reducts

    An empirical study of density and distribution functions for ant swarm optimized rough reducts by Pratiwi, Lustiana, Choo, Yun Huoy, Draman @ Muda, Azah Kamilah

    Published 2011
    “…Ant colony approach in Ant Swarm algorithm generates local solutions which satisfy the Gaussian distribution for global optimization using PSO algorithm. …”
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  15. 15
    Binary ant colony optimization algorithm in learning random satisfiability logic for discrete hopfield neural network

    Binary ant colony optimization algorithm in learning random satisfiability logic for discrete hopfield neural network by Gao, Yuan, Mohd Kasihmuddin, Mohd Shareduwan, Chen, Ju, Zheng, Chengfeng, Romli, Nurul Atiqah, Mansor, Mohd. Asyraf, Zamri, Nur Ezlin

    Published 2024
    “…This study introduced a novel ant colony optimization algorithm that implements the population selection strategy of the Estimation of Distribution Algorithm and a new pheromone updating formula. …”
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  16. 16
    Modified Parameters of Harmony Search Algorithm for Better Searching

    Modified Parameters of Harmony Search Algorithm for Better Searching by Nur Farraliza, Mansor, Abas, Z.A, Shibghatullah, A.S., Rahman, A.F.N.A

    Published 2017
    “…The contributions to this research are the HMCR parameter using step function while the fret spacing concept on guitars that is associated with mathematical formulae is also applied in the BW parameter. …”
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  17. 17
    A fuzzy adaptive teaching learning-based optimization strategy for generating mixed strength t-way test suites

    A fuzzy adaptive teaching learning-based optimization strategy for generating mixed strength t-way test suites by Din, Fakhrud

    Published 2019
    “…Addressing these issues, this thesis proposes a new TLBO variant based on a Mamdani-type fuzzy inference system, called adaptive TLBO (ATLBO), to permit adaptive selection of its global and local search operations. …”
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  18. 18
    Data-driven hybrid approaches for renewable power prediction toward grid decarbonization: Applications, issues and suggestions

    Data-driven hybrid approaches for renewable power prediction toward grid decarbonization: Applications, issues and suggestions by Hossain Lipu M.S., Miah M.S., Ansari S., Hannan M.A., Hasan K., Sarker M.R., Mahmud M.S., Hussain A., Mansor M.

    Published 2023
    Review
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  19. 19
    Feature optimization with metaheuristics for Artificial Neural Network-based chiller power prediction

    Feature optimization with metaheuristics for Artificial Neural Network-based chiller power prediction by Nor Farizan, Zakaria, Mohd Herwan, Sulaiman, Zuriani, Mustaffa

    Published 2025
    “…This research contributes a novel hybrid model, identifies key features for chiller power prediction, and establishes a benchmark for evaluating feature selection algorithms in building energy applications.…”
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  20. 20
    New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems

    New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems by Nor Shuhada, Ibrahim

    Published 2024
    “…Thirdly, the thesis validates the algorithm's performance on standard constrained single objective and multi objective benchmark test functions. …”
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