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  1. 1

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Tay, Kim Gaik, Huong, Audrey, Sathasivam, Saratha, Majahar Ali, Majid Khan

    Published 2023
    “…Inspired by evolutionary algorithms, which can iteratively find the nearoptimal solution, different Evolutionary Algorithms (EAs) were designed to optimize the producer output weight of the SRBFNN that corresponds to the embedded logic programming 2Satisfiability representation (SRBFNN2SAT). …”
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  2. 2

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

    Published 2023
    “…Inspired by evolutionary algorithms, which can iteratively find the nearoptimal solution, different Evolutionary Algorithms (EAs) were designed to optimize the producer output weight of the SRBFNN that corresponds to the embedded logic programming 2Satisfiability representation (SRBFNN2SAT). …”
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  3. 3

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majid Khan bin Majahar Ali, Majid Khan bin Majahar Ali

    Published 2023
    “…Inspired by evolutionary algorithms, which can iteratively find the nearoptimal solution, different Evolutionary Algorithms (EAs) were designed to optimize the producer output weight of the SRBFNN that corresponds to the embedded logic programming 2Satisfiability representation (SRBFNN2SAT). …”
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  4. 4

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

    Published 2023
    “…Inspired by evolutionary algorithms, which can iteratively find the nearoptimal solution, different Evolutionary Algorithms (EAs) were designed to optimize the producer output weight of the SRBFNN that corresponds to the embedded logic programming 2Satisfiability representation (SRBFNN2SAT). …”
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  5. 5

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

    Published 2023
    “…Inspired by evolutionary algorithms, which can iteratively find the nearoptimal solution, different Evolutionary Algorithms (EAs) were designed to optimize the producer output weight of the SRBFNN that corresponds to the embedded logic programming 2Satisfiability representation (SRBFNN2SAT). …”
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  6. 6

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

    Published 2023
    “…Inspired by evolutionary algorithms, which can iteratively find the nearoptimal solution, different Evolutionary Algorithms (EAs) were designed to optimize the producer output weight of the SRBFNN that corresponds to the embedded logic programming 2Satisfiability representation (SRBFNN2SAT). …”
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  7. 7

    Mussels wandering optimization algorithmn based training of artificial neural networks for pattern classification by Abusnaina, Ahmed A., Abdullah, Rosni

    Published 2013
    “…Traditional training algorithms have some drawbacks such as local minima and its slowness.Therefore, evolutionary algorithms are utilized to train neural networks to overcome these issues.This research tackles the ANN training by adapting Mussels Wandering Optimization (MWO) algorithm.The proposed method tested and verified by training an ANN with well-known benchmarking problems.Two criteria used to evaluate the proposed method were overall training time and classification accuracy.The obtained results indicate that MWO algorithm is on par or better in terms of classification accuracy and convergence training time.…”
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  8. 8

    Real-time optimal switching angle scheme for a cascaded H-Bridge inverter using Bonobo Optimizer by Abdul Wahab, Noor Izzri, Abdulsalam Taha, Taha, Hassan, Mohd Khair, Zaynal, Hussein I., Taha, Faris Hassan, Mohammed Hashim, Abdulghafor

    Published 2024
    “…The results demonstrate that the BO algorithm is the most accurate and fastest evolutionary algorithm for calculating optimal switching angles. …”
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  9. 9

    Optimization of RFID network planning for monitoring railway mechanical defects based on gradient-based Cuckoo search algorithm by Talib, Nihad Hasan

    Published 2020
    “…Finally, the third challenge is how to find the optimal evolutionary method for railway network planning to increase the RFID system performance. …”
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    Thesis
  10. 10

    Investigation of load variant under power distribution network reconfiguration using EPSO algorithm by Sulaima, Mohamad Fani, Wong, Kok Loong, Bohari, Zul Hasrizal, Mohd Nasir, Mohamad Na'im

    Published 2024
    “…Furthermore, the test result also indicated that the EPSO algorithm produced better results in terms of convergence time compared to the conventional PSO algorithm.…”
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  11. 11

    Optimization of multipurpose reservoir operation using evolutionary algorithms / Mohammed Heydari by Mohammed , Heydari

    Published 2017
    “…An improved particle swarm algorithm (HPSOGA) is used to solve complex problems of water resources optimization. …”
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    Thesis
  12. 12
  13. 13

    A DNR by Using Rank Evolutionary Particle Swarm Optimization for Power Loss Minimization by Sulaima, Mohamad Fani, Othman, Siti Atika, Jamri , Mohd Saifuzam, Omar, Rosli, Sulaiman , Marizan

    Published 2014
    “…The proposed method is a combination of the Particle Swarm Optimization (PSO) and the traditional Evolutionary Programming (EP) algorithm with a rejuvenation of the additional of ranking element. …”
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  14. 14
  15. 15

    Automatic generation of neural game controller using single and bi-objective evolutionary optimization algorithms for RTS Game by Chang, Kee Tong

    Published 2015
    “…The sub-objectives are: 1) to create preliminary optimization experiment with different crossover and mutation rates using GA and Feed-Forward Artificial Neural Networks (FFNN). …”
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  16. 16

    Optimal design of a 3D-printed scaffold using intelligent evolutionary algorithms by Asadi-Eydivand, M., Solati-Hashjin, M., Fathi, A., Padashi, M., Abu Osman, Noor Azuan

    Published 2016
    “…First, particle swarm optimization algorithm was implemented to obtain the optimum topology of the AANN. …”
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  17. 17

    An efficient anomaly intrusion detection method with evolutionary neural network by Sarvari, Samira

    Published 2020
    “…The third proposed method is a new Evolutionary Neural Network (ENN) algorithm with a combination of Genetic Algorithm and Multiverse Optimizer (GAMVO) as a training part of ANN to create efficient anomaly-based detection with low false alarm rate. …”
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  18. 18

    Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

    Published 2008
    “…Three programs have developed; Differential Evolution Neural Network (DENN), Genetic Algorithm Neural Network (GANN) and Particle Swarm Optimization with Neural Network (PSONN) to probe the impact of these methods on ANN learning using various datasets. …”
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    Thesis
  19. 19

    Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module by Koh J.S.P., Aris I.B., Ramachandaramurthy V.K., Bashi S.M., Marhaban M.H.

    Published 2023
    “…The representation approach has been implemented via a computer program in order to achieve optimized marking performance. This algorithm has been tested and implemented successfully via a dual-beam optical scanning module. � 2006 Asian Network for Scientific Information.…”
    Article
  20. 20

    Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module by Koh J.S.P., Aris I.B., Ramachandaramurthy V.K., Bashi S.M., Marhaban M.H.

    Published 2023
    “…The representation approach has been implemented via a computer program in order to achieve optimized marking performance. This algorithm has been tested and implemented successfully via a dual-beam optical scanning module. � 2006 Asian Network for Scientific Information.…”
    Article