Search Results - evolution programming (ep)

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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
    “…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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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
    “…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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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
    “…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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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
    “…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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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
    “…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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    Article
  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
    “…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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  7. 7
  8. 8

    Comparative study of optimal power flow using evolutionary programming and immune evolutionary programming technique in power system / Mohd Khairil Izwan Md Daim by Md Daim, Mohd Khairil Izwan

    Published 2006
    “…This study will utilize concept of Immune Evolutionary Programming (IEP) which is a combination of EP and AIS technique and compare the results to that obtained from Evolutionary Programming (EP) technique. …”
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  9. 9

    Self-evaluation of RTS Troop's performance by Chin Kim On, Chang Kee Tong, Jason Teo, Rayner Alfred, Wang Cheng, Tan Tse Guan

    Published 2015
    “…This paper demonstrates the research results obtained from a comparison of Evolutionary Programming (EP) and hybrid Differential Evolution (DE) and Feed Forward Neural Network (FFNN) algorithms in the Real Time Strategy (RTS) computer game, namely Warcraft III. …”
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    Non-Indexed Article
  10. 10

    Minimization of power loss by evolutionary programming using Thyristor Controlled Series Compensators (TCSC) / Fazleza Abdul Latiff by Abdul Latiff, Fazleza

    Published 2007
    “…This approach is done by using Evolutionary Programming (EP) technique. EP search for the optimal solution by evolving a population of candidate solutions, over a number of generations or iterations. …”
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  11. 11

    Exploration of mutation step sizes in the automated evolution of printable free-form 3D objects by Teo, Jason Tze Wi, Jia, Hui Ong

    Published 2016
    “…In this study, an EA in the form of Evolutionary Programming (EP) is used to automatically evolve 3D objects generated by Gielis’ Superformula. …”
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  12. 12

    Empirical Evaluation of Mutation Step Size in Automated Evolution of Non-Target-Based 3D Printable Objects by Jia Hui Ong, Jason Teo

    Published 2015
    “…In this study, an EA in the form of Evolutionary Programming (EP) is used to automatically evolve 3D objects generated by Geilis’s Superformula. …”
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  13. 13

    Global optimal analysis of variant genetic operations in solar tracking by Fam D.F., Koh S.P., Tiong S.K., Chong K.H.

    Published 2023
    “…Genetic Algorithms (GAs), Evolution Strategies (ES), Evolutionary Programming (EP) and Genetic Programming (GP) are some of the best known types of Evolutionary Algorithm (EA)where it is a class of global search algorithms inspired by natural evolution. …”
    Article
  14. 14

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

    Published 2015
    “…The proposed EC methods are Genetic Algorithm (GA), Differential Evolution (DE), Evolutionary Programming (EP), and Pareto-based Differential Evolution (PDE). …”
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  15. 15

    Tap changer optimisation using embedded differential evolutionary programming technique for loss control in power system by Faris A., Musirin I., Jelani S., Ismail S.A., Mansor M.H., Senthil Kumar A.V.

    Published 2023
    “…A new optimization technique termed as embedded differential evolutionary programming (EDEP) is proposed, which integrates the traditional differential evolution (DE) and evolutionary programming (EP). …”
    Article
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    Evolutionary symbiotic organisms search technique in power scheduling for loss control in power transmission system by Farid N.M.M., Musirin I., Hannon N.H.S., Amroune M., Othman Z., Othman M.M., Shaaya S.A., Zamani M.K.M., Aminuddin N.

    Published 2023
    “…Symbiotic Organisms Search (SOS) integrated with Evolutionary Programming (EP) is proposed for solving power scheduling problem in the attempt to control the loss values in electric power system. …”
    Article
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    Multi-DGPV Planning Using Artificial Intelligence by Abdullah A., Musirin I., Othman M.M., Rahim S.R.A., Sentilkumar A.V.

    Published 2024
    “…The IIMFEP approach is compared against Evolutionary Programming (EP), Artificial Immune System (AIS), and Moth Flame Optimization (MFO) and validated using the IEEE 118-Bus Radial Distribution Systems (RDS). …”
    Article
  18. 18

    Voltage constrained optimal power flow based using genetic algorithm by Yassir Asnawi, Teuku Hasannuddin

    Published 2015
    “…Effectiveness of the proposed method was tested on IEEE 30 bus system and it has been compared to other optimization of power fl ow using other methods, for example the Evolutionary Programming (EP), Differential Evolution (DE) and Particle Swarm Optimization (PSO) methods. …”
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  19. 19

    An improved grey wolf with whale algorithm for optimization functions by Asgher, Hafiz Maaz

    Published 2022
    “…Since its inception in 2014, GWO is able to successfully solve several optimization problems and has shown better convergence than the Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Differential Evolution (DE), and Evolutionary Programming (EP). …”
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