Search Results - (( pattern classification swarm algorithm ) OR ( evolution optimization based algorithm ))

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  1. 1

    Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals by Too, Jing Wei

    Published 2020
    “…Therefore, this thesis aims to solve the feature selection problem in EMG signals classification and improve the classification performance of EMG pattern recognition system. …”
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    Thesis
  2. 2

    Swarm negative selection algorithm for electroencephalogram signals classification by Sahel Ba-Karait, Nasser Omer, Shamsuddin, Siti Mariyam, Sudirman, Rubita

    Published 2009
    “…Such automated systems must rely on robust and effective algorithms for detection and prediction. Approach: The proposed detection system of epileptic seizure in EEG signals is based on Discrete Wavelet Transform (DWT) and Swarm Negative Selection (SNS) algorithm. …”
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    Article
  3. 3

    Neural Network Training Using Hybrid Particle-move Artificial Bee Colony Algorithm for Pattern Classification by Nuaimi, Zakaria Noor Aldeen Mahmood Al, Abdullah, Rosni

    Published 2017
    “…Therefore, evolutionary algorithms like the Swarm Intelligence (SI) algorithms have been employed in ANNT to overcome such issues. …”
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  4. 4

    Neural network training using hybrid particle-move artificial bee colony algorithm for pattern classification by Al Nuaimi, Zakaria Noor Aldeen Mahmood, Abdullah, Rosni

    Published 2017
    “…In this work, we aimed to highlight the performance of the Hybrid Particle-move Artificial Bee Colony (HPABC) algorithm by applying it on the ANNT application.The performance of the HPABC algorithm was investigated on four benchmark pattern-classification data sets and the results were compared with other algorithms.The results obtained illustrate that HPABC algorithm can efficiently be used for ANNT.HPABC outperformed the original ABC and PSO as well as other state-of-art and hybrid algorithms in terms of time, function evaluation number and recognition accuracy.…”
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    Article
  5. 5

    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
  6. 6

    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
  7. 7

    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
  8. 8

    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
  9. 9

    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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    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
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    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…In order to address the challenges that mentioned above in this study, in the first phase, a novel architecture based on ensemble feature selection techniques include Modified Binary Bat Algorithm (NBBA), Binary Quantum Particle Swarm Optimization (QBPSO) Algorithm and Binary Quantum Gravita tional Search Algorithm (QBGSA) is hybridized with the Multi-layer Perceptron (MLP) classifier in order to select relevant feature subsets and improve classification accuracy. …”
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    Thesis
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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
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    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