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  1. 1

    Discretization of crack propagation on parallel computing : complexity and parallel algorithms with source code by Alias, Norma, Islam, Md. Rajibul

    Published 2010
    “…Parallel algorithm is used by Parallel Virtual Machine (PVM) software tool to capture the visualization of the overall extension and the stress distribution in a linearly tapered bar of circular section with an end load. …”
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  2. 2

    Discretization of crack propagation on parallel computing: complexity and parallel algorithms with source code by Alias, Norma, Islam, Md. Rajibul

    Published 2010
    “…Parallel algorithm is used by Parallel Virtual Machine (PVM) software tool to capture the visualization of the overall extension and the stress distribution in a linearly tapered bar of circular section with an end load. …”
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  3. 3

    Implementation of a parallel XTS encryption mode of operation by Alomari, Mohammad Ahmed, Samsudin, Khairulmizam, Ramli, Abdul Rahman

    Published 2014
    “…The parallel XTS algorithm has shown a speedup of 1.80, with 90% efficiency, faster than the sequential algorithm. …”
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  4. 4

    Parallel block backward differentiation formulas for solving ordinary differential equations. by Othman, Khairil Iskandar, Ibrahim, Zarina Bibi, Suleiman, Mohamed

    Published 2008
    “…Numerical results are given to compare the speedup and efficiency of parallel algorithm and that of sequential algorithm.…”
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  5. 5

    Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

    Published 2008
    “…These algorithms can be used successfully in many applications requiring the optimization of a certain multi-dimensional function. …”
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  6. 6
  7. 7

    Empirical analysis of parallel-NARX recurrent network for long-term chaotic financial forecasting by Abdulkadir, S.J., Yong, S.-P.

    Published 2014
    “…This paper presents an empirical long term chaotic financial forecasting approach using Parallel non-linear auto-regressive with exogenous input (P-NARX) network trained with Bayesian regulation algorithm. …”
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  8. 8

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

    Published 2020
    “…In this regard, this thesis proposes five FS methods for efficient EMG signals classification. The first method is the Binary Tree Growth Algorithm (BTGA), which implements a hyperbolic tangent function to convert the Tree Growth Algorithm into the binary version. …”
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  9. 9

    Control Input Converter for Robot’s Leg Joint with Parallel Actuation Configuration by Addie Irawan, Hashim, Hoe, Lih Jiun, M. M., Alam

    Published 2015
    “…This paper presents the proposed control input converter (CiC) for robot leg's joint control with parallel actuation. The parallel actuation commonly used in heavy machine such as backhoe and bulldozer. …”
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  10. 10

    Direct Block Methods for Solving Special Second Order Ordinary Differential Equations and Their Parallel Implementations by Yap, Lee Ken

    Published 2008
    “…Hence the last part of the thesis discusses the parallel execution of the codes. The parallel algorithms are written in C language and implemented on Sun Fire V1280 distributed memory system. …”
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  11. 11

    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
    “…DE is very sensitive to its parameter settings and mutation strategy; thus, this study aims to investigate these settings with the diverse versions of adaptive DE algorithms. This study has two main objectives: (1) to present an extension for the original taxonomy of evolutionary algorithms (EAs) parameter settings that has been overlooked by prior research and therefore minimize any confusion that might arise from the former taxonomy and (2) to investigate the various algorithmic design schemes that have been used in the different variants of adaptive DE and convey them in a new classification style. …”
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  12. 12

    Effective EEG channels for emotion identification over the brain regions using differential evolution algorithm by Al-Qazzaz, Noor Kamal, Sabir, Mohannad K., Md. Ali, Sawal Hamid, Ahmad, Siti Anom, Grammer, Karl

    Published 2019
    “…Furthermore, the right and left occipital channels may help in identifying happiness, sadness, surprise and neutral emotional states. The DEFS_Ch algorithm raised the linear discriminant analysis (LDA) classification accuracy from 80% to 86.85%, indicating that DEFS_Ch may offer a useful way for reliable enhancement of the detection of different emotional states of the brain regions.…”
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  13. 13

    Intersection Features For Android Botnet Classification by Ismail, Najiahtul Syafiqah, Yusof, Robiah, Saad, Halizah, Abdollah, Mohd Faizal, Yusof, Robiah

    Published 2019
    “…The Chi Square was used to select the most significant permissions, then the classification algorithms like Naïve Bayes and Decision Tree were used to classify the Android apps as botnet or benign apps. …”
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  14. 14

    Feature selection optimization using hybrid relief-f with self-adaptive differential evolution by Zainudin, Muhammad Noorazlan Shah, Sulaiman, Md. Nasir, Mustapha, Norwati, Perumal, Thinagaran, Ahmad Nazri, Azree Shahrel, Mohamed, Raihani, Abd Manaf, Syaifulnizam

    Published 2017
    “…Hence, feature selection is embedded to select the most meaningful features based on their rank. Differential evolution (DE) is one of the evolutionary algorithms that are widely used in various classification domains. …”
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  15. 15

    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures by Koohi, Sina Zangbari

    Published 2020
    “…These complex systems have designed to solve various types of problems from different areas, resulting in high-demanding Heterogeneous Parallel Applications (HPAs). HPAs use parallel processors and assist in parallel execution of tasks with complex interdependency between data and operations. …”
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  16. 16

    A comparison study between integrated OBFARX-NN and OBF-NN for modeling of nonlinear systems in extended regions of operation by Zabiri, H., Ariff, M., Tufa, L.D., Ramasamy, M.

    Published 2014
    “…A residuals-based sequential identification algorithm using parallel integration of linear Orthornormal basis filters-Auto regressive with exogenous input (OBFARX) and a nonlinear neural network (NN) models is developed. …”
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  17. 17

    EMG Feature Selection And Classification Using A Pbest-Guide Binary Particle Swarm Optimization by Too, Jing Wei, Tee, Wei Hown, Abdullah, Abdul Rahim, Mohd Saad, Norhashimah

    Published 2019
    “…In order to measure the effectiveness of PBPSO, binary particle swarm optimization (BPSO), genetic algorithm (GA), modified binary tree growth algorithm (MBTGA), and binary differential evolution (BDE) were used for performance comparison. …”
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  18. 18

    A New Quadratic Binary Harris Hawk Optimization For Feature Selection by Abdullah, Abdul Rahim, Too, Jing Wei, Mohd Saad, Norhashimah

    Published 2019
    “…A comparative study is conducted to compare the effectiveness of QBHHO with other feature selection algorithms such as binary differential evolution (BDE), genetic algorithm (GA), binary multi-verse optimizer (BMVO), binary flower pollination algorithm (BFPA), and binary salp swarm algorithm (BSSA). …”
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  19. 19

    Integrated OBF-NN models for extrapolation enhancement in conventional neural networks for nonlinear systems by H., Zabiri, M., Ramasamy, Lemma D, Tufa, Maulud, Abdulhalim

    Published 2011
    “…A residuals-based sequential identification algorithm using parallel integration of linear Orthornormal basis filters (OBF) and a nonlinear feedforward (MLP) NN model is used and applied to the nonlinear Van de Vusse reactor. …”
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  20. 20

    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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