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  1. 1
    Enhancing three variants of harmony search algorithm for continuous optimization problems

    Enhancing three variants of harmony search algorithm for continuous optimization problems by Alomoush, Alaa A., Alsewari, Abdulrahman A., Kamal Z., Zamli, Alrosan, Ayat, Alomoush, Waleed, Alissa, Khalid

    Published 2021
    “…A convergence rate graph is also used to show the overall performance of the new algorithms.…”
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  2. 2
    Development and applications of metaheuristic algorithms in engineering design and structural optimization / Ali Sadollah

    Development and applications of metaheuristic algorithms in engineering design and structural optimization / Ali Sadollah by Ali, Sadollah

    Published 2013
    “…The obtained optimization results shows that the proposed new metaheuristic algorithms are capable of offering faster convergence rate in addition to offering better optimal solutions compared to other optimizers. …”
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  3. 3
    Improvement and application of particle swarm optimization algorithm

    Improvement and application of particle swarm optimization algorithm by Deevi, Durga Praveen, Kodadi, Sharadha, Allur, Naga Sushma, Dondapati, Koteswararao, Chetlapalli, Himabindu, Perumal, Thinagaran

    Published 2025
    “…An ideal assignment technique assigns new duties to each functioning robot, followed by evolutionary algorithms and Particle Swarm Optimization (PSO) to design pathways to the reconfigured positions. …”
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  4. 4
    Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms

    Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms by Ridha, Hussein Mohammed

    Published 2020
    “…The IEM algorithm uses the attraction-repulsion mechanism to change the positions of solutions towards the optimality. …”
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  5. 5
    Optimization of Simultaneous Scheduling for Machines and Automated Guided Vehicles Using Fuzzy Genetic Algorithm

    Optimization of Simultaneous Scheduling for Machines and Automated Guided Vehicles Using Fuzzy Genetic Algorithm by Badakhshian, Mostafa

    Published 2009
    “…There is a heuristic algorithm to assign the AGVs to the operations. As the main findings, the performance of GA in simultaneous scheduling of AGVs and machines is enhanced by using proposed method, furthermore a new mutation operator has been proposed. …”
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  6. 6
    The fusion of particle swarm optimization (PSO) and interior point method (IPM) as cooperative movement control algorithm in Swarm Robotics / Dada Emmanuel Gbenga

    The fusion of particle swarm optimization (PSO) and interior point method (IPM) as cooperative movement control algorithm in Swarm Robotics / Dada Emmanuel Gbenga by Dada Emmanuel, Gbenga

    Published 2016
    “…Secondly, we compared the performance of our new algorithm pdAPSO with APSO, and PSO using 7 benchmark functions. …”
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  7. 7
    A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem

    A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

    Published 2016
    “…The main keys of the new classifier are based on the new kernel method, new learning metric and a new optimization algorithm in order to optimize the SVM decision function. …”
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  8. 8
    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
    “…Finally, propose a new method of obtaining optimal parameters dropping functions for Random Early Detection (RED) algorithm. …”
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  9. 9
    Crossover and mutation operators of real coded genetic algorithms for global optimization problems

    Crossover and mutation operators of real coded genetic algorithms for global optimization problems by Lim, Siew Mooi

    Published 2016
    “…The rationale behind developing algorithms using real encoding of chromosome representations is the limitations of binary encoding. …”
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  10. 10
    Opposition-Based Learning Binary Bat Algorithm as Feature Selection Approach in Taguchi's T-Method

    Opposition-Based Learning Binary Bat Algorithm as Feature Selection Approach in Taguchi's T-Method by Marlan Z.M., Jamaludin K.R., Harudin N.

    Published 2024
    “…Thus, this study proposed an Opposition-based Learning Binary Bat Algorithm as the feature selection technique in the T-method. …”
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  11. 11
    PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM

    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
    “…To overcome these limitations, there have been attempts to use genetic algorithm (GA) to optimize some of these parameters. …”
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  12. 12
    Weight Optimization in Recurrent Neural Networks with Hybrid Metaheuristic Cuckoo Search Techniques for Data Classification

    Weight Optimization in Recurrent Neural Networks with Hybrid Metaheuristic Cuckoo Search Techniques for Data Classification by Nawi, N.M., Khan, A., Rehman, M.Z., Chiroma, H., Herawan, T.

    Published 2015
    “…The proposed CSERN and CSBPERN algorithms are compared with artificial bee colony using BP algorithm and other hybrid variants algorithms. …”
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  13. 13
    New learning algorithm based on Hidden Markov Model (HMM) as stochastic modelling for pattern calssification

    New learning algorithm based on Hidden Markov Model (HMM) as stochastic modelling for pattern calssification by Balakrishnan, Malarvili, Ting, Chee Ming, Shaikh Salleh, Sheikh Hussain

    Published 2009
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  14. 14
    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 second taxonomy is a new taxonomy proposed to classify the adaptive DE algorithms in particular into two categories (DE with adaptive parameters and DE with adaptive parameters and strategies) considering the adaptive components used in this algorithm. …”
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  15. 15
    A new variant of black hole algorithm based on multi population and levy flight for clustering problem

    A new variant of black hole algorithm based on multi population and levy flight for clustering problem by Haneen Abdul Wahab, Abdul Raheem

    Published 2020
    “…Furthermore, the results revealed a high convergence rate, upon which the algorithm’s performance was subjected to data clustering problems and investigated using six real datasets. …”
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  16. 16
    Nomadic people optimizer (NPO) for large-scale optimization problems

    Nomadic people optimizer (NPO) for large-scale optimization problems by Mohamd Salih, Sinan Qahtan

    Published 2019
    “…Researchers have in the past few decades resorted to several methods that are inspired from complex optimization problems. …”
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  17. 17
    Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach

    Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach by Wan Solehah, Wan Ahmad

    Published 2022
    “…The other one is the network training’s environment optimization that is done through hyperparameter optimization by selecting and fine-tuning high impact parameters which include Optimizer, Learning Rate and Dropout to reduce error rate (loss function). …”
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  18. 18
    Implementation of Symmetric Rank-One Methods for Unconstrained Optimization

    Implementation of Symmetric Rank-One Methods for Unconstrained Optimization by Khiyaban, Farzin Modarres

    Published 2010
    “…We prove that the new method possesses global convergence. The rate of convergence of such algorithms are also discussed. …”
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  19. 19
    An ensemble method with cost function on churn prediction

    An ensemble method with cost function on churn prediction by Mohd Khalid, Awang, Mohammad Afendee, Mohamed, Mokhairi, Makhtar

    Published 2019
    “…The combination of ensemble classifier is calculated based on the simple majority voting algorithm. The performance measure used in determining the optimal subset of classifiers is the combination of Accuracy (ACC), True Negative Rate (TNR) and True Positive Rate (TPR). …”
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  20. 20
    Numerical methods for nonlinear optimal control problems using haar wavelet operational matrices / Waleeda Swaidan Ali

    Numerical methods for nonlinear optimal control problems using haar wavelet operational matrices / Waleeda Swaidan Ali by Waleeda Swaidan, Ali

    Published 2015
    “…To establish a direct method, an efficient new algorithm is proposed to solve nonlinear optimal control problems with a finite time horizon under inequality constraints. …”
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