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  1. 1
    Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions

    Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions by Abbas, Iraq Tareq

    Published 2018
    “…The second technique is to solve bi-objective functions by using the BOBAT algorithm. The third technique is an integration of BOGSA with BOBAT to produce a BOGSBAT algorithm. …”
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  2. 2
    An efficient method for determining all the extreme points of function with one variable

    An efficient method for determining all the extreme points of function with one variable by Pandiya, Ridwan

    Published 2014
    “…The algorithm is the combination of the filled function's algorithm and Inner Iteration algorithm, called IRH's algorithm, in which Inner Iteration algorithm works at the domain which is usually ignored by filled function's algorithm.…”
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  3. 3
    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    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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  4. 4
    Determining the preprocessing clustering algorithm in radial basis function neural network

    Determining the preprocessing clustering algorithm in radial basis function neural network by S.L. Ang, H.C. Ong, H.C. Law

    Published 2008
    “…Three types of method used in this study to find the centres include random selections, K-means clustering algorithm and also K-median clustering algorithm. …”
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  5. 5
    Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm

    Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm by Dalatu, Paul Inuwa

    Published 2018
    “…It shows that the IQR-HEOM method is more efficient to rectify the problem caused by using range in HEOM. …”
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  6. 6
    Bees algorithm enhanced with Nelder and Mead method for numerical function optimisation

    Bees algorithm enhanced with Nelder and Mead method for numerical function optimisation by Kamaruddin, Shafie, Bahari, Muhammad Syahril, Pham, Duc Truong, Mohd Amin Hamzas, Mohd Fidzwan, Zakaria, S

    Published 2019
    “…The performance of the proposed algorithm was tested on a set of seventeen well-known benchmark functions. …”
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  7. 7
    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    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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  8. 8
    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    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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  9. 9
    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    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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  10. 10
    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    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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  11. 11
    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    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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  12. 12
    Fuzzy modeling using Bat Algorithm optimization for classification

    Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

    Published 2018
    “…As a result, the highest average accuracy generated which is 96.91% by using WBCD dataset. The average accuracy of Bat Algorithm is comparing with other methods. …”
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  13. 13
    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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  14. 14
    Finding the root of nonlinear function using five bracketing method / Nur Afiqah Mohamed Azhar

    Finding the root of nonlinear function using five bracketing method / Nur Afiqah Mohamed Azhar by Mohamed Azhar, Nur Afiqah

    Published 2019
    “…Therefore, numerical method in the form of bracketing method is often used to find only the approximate root of the function. …”
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  15. 15
    A firefly algorithm based hybrid method for structural topology optimization

    A firefly algorithm based hybrid method for structural topology optimization by Gebremedhen, H.S., Woldemichael, D.E., Hashim, F.M.

    Published 2020
    “…Since the direct application of the firefly algorithm cannot generate connected topologies, outputs from the firefly algorithm were used as an initial input material distribution for the OC method. …”
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  16. 16
    The efficiency of conjugate gradient methods with global convergence / Siti Nur Hafiza Shamsudin

    The efficiency of conjugate gradient methods with global convergence / Siti Nur Hafiza Shamsudin by Shamsudin, Siti Nur Hafiza

    Published 2019
    “…The global convergence result is established using exact line searches. Numerical result shows that algorithm 2 which is one of the proposed CG methods is more efficiency when compared to other algorithms.…”
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  17. 17
    Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems

    Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems by Zulkifli, Munierah, Abd Rahmin, Nor Aliza, Wah, June Leong

    Published 2023
    “…This paper proposes a new SGD algorithm with modified stepsize that employs function scaling strategy. …”
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  18. 18
    Optimization of mycelium growth using genetic algorithm for multi-objective functions

    Optimization of mycelium growth using genetic algorithm for multi-objective functions by Muhamad Faiz, Abu Bakar

    Published 2019
    “…To solve this issues, multi-objective genetic algorithm was chosen as the methodology for this project, specifically using NSGA-ii algorithm. …”
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  19. 19
    Genetic Algorithms In Optimizing Membership Function For Fuzzy Logic Controller

    Genetic Algorithms In Optimizing Membership Function For Fuzzy Logic Controller by Ismail, H. Muh Yusuf

    Published 2010
    “…Thus it is important to select the accurate membership functions but these methods possess one common weakness where conventional FLC use membership function and control rules generated by human operator. …”
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  20. 20
    Global gbest guided-artificial bee colony algorithm for numerical function optimization

    Global gbest guided-artificial bee colony algorithm for numerical function optimization by Shah, Habib, Tairan, Nasser, Garg, Harish, Ghazali, Rozaida

    Published 2018
    “…Numerous computational algorithms are used to obtain a high performance in solving mathematics, engineering and statistical complexities. …”
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