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  1. 1

    Multi-Objectives Memetic Discrete Differential Evolution Algorithm for Solving the Container Pre-Marshalling Problem by Mustafa, Hossam M. J., Ayob, Masri, Ahmad Nazri, Mohd Zakree, Abu-Taleb, Sawsan

    Published 2019
    “…This demonstrates that using the multi-objectives approach with a combination of the Discrete Differential Evolution mutation and the Memetic Algorithm evolutionary is a suitable approach for solving multi-objectives CPMP.…”
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    Article
  2. 2

    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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  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, 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
  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, 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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  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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  6. 6

    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
  7. 7

    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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    Article
  8. 8

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

    Published 2015
    “…To carry out this study, five different mutation step sizes were used and each mutation step size will be run for five times. …”
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  9. 9

    Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy by Al-Dabbagh, Rawaa Dawoud, Neri, Ferrante, Idris, Norisma, Baba, Mohd Sapiyan

    Published 2018
    “…The proposed design framework provides readers with the main steps required to integrate any proposed meta-algorithm into parameter and/or strategy adaptation schemes.…”
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  10. 10

    Resource allocation in coordinated multipoint long term evolution-advanced networks by Katiran, Norshidah

    Published 2015
    “…ORA is formulated based on Lagrangian method and optimized using Particle Swarm Optimization (PSO). The design of CLD-ORA algorithm is an enhancement of the ORA algorithm with resource block (RB) scheduling scheme at medium access control (MAC) layer. …”
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    Thesis
  11. 11

    Optimized differential evolution algorithm for linear frequency modulation radar signal denoising by Al-Dabbagh, Mohanad Dawood Hasan

    Published 2013
    “…We refer to the new DE algorithm as random variable length crossover DE (rvlx- DE) algorithm. …”
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    Thesis
  12. 12

    Load balancing in 4G long term evolution / Marvin Hendary by Hendary, Marvin

    Published 2013
    “…Long Term Evolution (LTE) and LTE-Advanced is the next major step towards 4th generation of mobile communications. …”
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    Thesis
  13. 13
  14. 14

    Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation by Ahmadipour, Masoud

    Published 2019
    “…Furthermore, to evaluate the efficiency of the proposed modified differential evolution for the training of ridgelet probabilistic neural network, four statistical search techniques, namely, particle swarm optimization, genetic algorithm, simulated angling, and classical differential evolution are used and their results are compared. …”
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    Thesis
  15. 15

    Genetic algorithm to optimize routing problem modelled as the travelling salesman problem by Muhammad Azrul Faiz , Nor Adzmi

    Published 2013
    “…Genetic algorithm conceptually follows steps inspired by the biological process of evolution. …”
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    Undergraduates Project Papers
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  17. 17

    Performance comparison of downlink packet scheduling algorithms in LTE network by Algharem, Mohd, Omar, Mohd Hasbullah, Alghamdi, Muhammed I., Budiarto, Rahmat

    Published 2014
    “…Different traffic types are used, and Simulation results show that in video traffic, FLS and EXP algorithms provide a higher system throughput compared to other algorithms while keeping the delay and packet loss ratio small. …”
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    Conference or Workshop Item
  18. 18

    A Bayesian parameter learning procedure for nonlinear dynamical systems via the ensemble Kalman filter by Ur Rehman, M.J., Dass, S.C., Asirvadam, V.S.

    Published 2018
    “…Within the parameter learning steps, the MCMC algorithm requires to perform state estimation for which the target distribution is constructed by using the Ensemble Kalman filter (EnKF). …”
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  19. 19

    Adaptive-model based self-tuning generalized predictive control of a biodiesel reactor / Ho Yong Kuen by Ho, Yong Kuen

    Published 2011
    “…Traditionally, the Recursive Least Squares (RLS) algorithm was used in the Generalized Predictive Control (GPC) framework solely for model adaptation purposes. …”
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    Thesis
  20. 20

    Development Of Human Skin Detection Algorithm Using Multilayer Perceptron Neural Network And Clustering Method by Al-Mohair, Hani Kaid Saif

    Published 2017
    “…Additionally, the effect of combining texture information with color information is investigated with the aim of boosting the performance of skin classifiers. The Differential Evolution Algorithm (DE) is used in this work to select the optimum color and texture information to achieve the optimum response. …”
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    Thesis