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  1. 1

    Genetic ensemble biased ARTMAP method of ECG-Based emotion classification by Loo, C.K., Liew, W.S., Sayeed, M.S.

    Published 2012
    “…The optimal combination of λ and training sequence can be computed efficiently using a genetic permutation algorithm. The best combinations were selected to train individual ARTMAPs as voting members, and the final class predictions were determined using probabilistic ensemble voting strategy. …”
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    Conference or Workshop Item
  2. 2

    JPEG Image Encryption Using Combined Reversed And Normal Direction-Distorted Dc Permutation With Key Scheduling Algorithm-Based Permutation by Abu, Ahmad Zaidee

    Published 2008
    “…The proposed approach uses a frequency domain combinational framework of coefficients scrambling with Key Scheduling Algorithm based (KSA-based) permutation. …”
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    Thesis
  3. 3

    Reliably optimal PMU placement using disparity evolution-based genetic algorithm by Matsukawa, Yoshiaki, Othman, Mohammad Lutfi, Watanabe, Masayuki, Mitani, Yasunori

    Published 2017
    “…In this paper, Disparity Evolution-type Genetic Algorithm (DEGA) based on disparity theory of evolution is applied. …”
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    Article
  4. 4

    A refined differential evolution algorithm for improving the performance of optimization process by A. R., Yusoff, Nafrizuan, Mat Yahya

    Published 2011
    “…DE is developed based on an improved Genetic Algorithm and come with different strategies for faster optimization. …”
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    Conference or Workshop Item
  5. 5

    A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising by Al-Dabbagh, Mohanad Dawood, Al-Dabbagh, Rawaa Dawoud, Raja Abdullah, Raja Syamsul Azmir, Hashim, Fazirulhisyam

    Published 2015
    “…The main intention of this study was to investigate the development of a new optimization technique based on the differential evolution (DE) algorithm, for the purpose of linear frequency modulation radar signal de-noising. …”
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    Article
  6. 6

    New algorithm for listing all permutations by Ibrahim, Haslinda, Omar, Zurni, Mohd Rohni, Azizah

    Published 2010
    “…The new algorithm has advantages over the other methods due to its simplicity and easy to use.…”
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    Article
  7. 7

    Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain by Mohamad Zihin , Mohd Zain

    Published 2018
    “…BSA gave the best overall performance by showing improved solutions and more robust convergence in comparison with various metaheuristics used in this work. Multi-objective optimization problems are also addressed by proposing a modified multi-criterion optimization algorithm based on a Pareto-based Particle Swarm Optimization (PSO) algorithm called Multi-Objective Particle Swarm Optimization (MOPSO). …”
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    Thesis
  8. 8

    Broadening selection competitive constraint handling algorithm for faster convergence by Shaikh, T.A., Hussain, S.S., Tanweer, M.R., Hashmani, M.A.

    Published 2020
    “…In this study, the BSCCH algorithm has been coupled with Differential Evolution algorithm as a proof of concept because it is found to be an efficient algorithm in the literature for constrained optimization problems. …”
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    Article
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  10. 10

    Improving the security of LBlock lightweight algorithm using bit permutation by AlDabbagh, Sufyan Salim Mahmood, Alshaikhli, Imad Fakhri Taha

    Published 2013
    “…LBlock uses word permutation to do the diffusion while this research uses bit permutation to increase the number of active Substitution box (S-box). …”
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    Proceeding Paper
  11. 11

    New recursive circular algorithm for listing all permutations by Karim, Sharmila, Omar, Zurni, Ibrahim, Haslinda, Othman, Khairil Iskandar, Suleiman, Mohamed

    Published 2014
    “…Linear array of permutations is hard to be factorised. However, by using a starter set, the process of listing the permutations becomes easy. …”
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    Article
  12. 12

    New recursive circular algorithm for listing all permutations by Karim, Sharmila, Omar, Zurni, Ibrahim, Haslinda, Othman, Khairil Iskandar, Suleiman, Mohamed

    Published 2014
    “…Linear array of permutations is hard to be factorized.However, by using a starter set, the process of listing the permutations becomes easy. …”
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    Article
  13. 13

    Crossover-first differential evolution for improved global optimization in non-uniform search landscapes by Teo, Jason Tze Wi, Mohd Hanafi Ahmad Hijazi, Hui, Keng Lau, Salmah Fattah, Aslina Baharum

    Published 2015
    “…The differential evolution (DE) algorithm is currently one of the most widely used evolutionary-based optimizers for global optimization due to its simplicity, robustness and efficiency. …”
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    Article
  14. 14

    Starter Set Generation Based on Factorial Numbers for Half Wing of Butterfly Representation by Karim, Sharmila, Ibrahim, Haslinda

    Published 2021
    “…This paper presents the use of factorial numbers for generating starter sets where starter sets are used for listing permutation. …”
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    Article
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    Hybrid differential evolution-particle swarm optimization algorithm for multi objective urban transit network design problem with homogeneous buses by Tarajo, Buba Ahmed, Lee, Lai Soon

    Published 2019
    “…This paper proposes a hybrid differential evolution with particle swarm optimization (DE-PSO) algorithm to solve the UTNDP, aiming to simultaneously optimize route configuration and service frequency with specific objectives in minimizing both the passengers’ and operators’ costs. …”
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    Article
  18. 18

    Nonlinear identification of a small scale unmanned helicopter using optimized NARX network with multiobjective differential evolution by Tijani, Ismaila B., Akmeliawati, Rini, Legowo, Ari, Budiyono, Agus

    Published 2014
    “…This study proposes a hybrid of conventional back propagation training algorithm for the NARX network and multiobjective differential evolution (MODE) algorithm for identification of a nonlinear model of an unmanned small scale helicopter from experimental flight data.The proposed hybrid algorithm was able to produce models with Pareto-optimal compromise between the design objectives. …”
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    Article
  19. 19

    Robust multi-user detection based on hybrid grey wolf optimization by Ji, Yuanfa, Fan, Z ., Sun, X., Wang, S., Yan, S., Wu, S., Fu, Q., Kamarul Hawari, Ghazali

    Published 2020
    “…The simulation results show that the iteration times of the multi-user detector based on the proposed algorithm is less than that of genetic algorithm, differential evolution algorithm and Grey wolf optimization algorithm, and has the lower BER.…”
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    Book Chapter
  20. 20

    Investigation and validation of an eleven level symmetric modular multilevel inverter using grey wolf optimization and differential evolution control algorithm for solar PV applica... by Stonier, A.A., Chinnaraj, G., Kannan, R., Mani, G.

    Published 2021
    “…Purpose: This paper aims to examine the design and control of a symmetric multilevel inverter (MLI) using grey wolf optimization and differential evolution algorithms. Design/methodology/approach: The optimal modulation index along with the switching angles are calculated for an 11 level inverter. …”
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    Article