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  1. 1

    Coil Optimization using Metaheuristic Techniques for Wireless Charging of Electric Vehicles - A Comparative Analysis. by Imtiaz T., Elsanabary A., Mekhilef S., Mubin M.B., Soon T.K., Aziz N.F.A.

    Published 2024
    “…Differential Evolution (DE), Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) optimization algorithms are used to obtain the lengths of all the turns of the transmitter coil. …”
    Conference Paper
  2. 2

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

    Published 2018
    “…An improved version of Differential Evolution (DE) namely Backtracking Search Algorithm (BSA) is applied to several fed batch fermentation problems and its performance is compared with recent emerging metaheuristics such as Artificial Algae Algorithm (AAA), Artificial Bee Colony (ABC), Covariance Matrix Adaptation Evolution Strategy (CMAES) and DE. …”
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    Thesis
  3. 3

    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
  4. 4

    Comparative analysis of spiral dynamic algorithm and artificial bee colony optimization for position control of flexible link manipulators by Nor Maniha, Abdul Ghani, Nizaruddin, M. Nasir, Azrul Azim, Abdullah Hashim

    Published 2024
    “…This study aims to evaluate the effectiveness of two optimization algorithms, artificial bee colony (ABC) and spiral dynamic algorithm (SDA), in controlling the position of a flexible-link manipulator. …”
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    Article
  5. 5

    An application of grey wolf optimizer for commodity price forecasting by Mustaffa, Zuriani, Sulaiman, Mohd Herwan, Yusof, Yuhanis

    Published 2015
    “…Over the recent decades, there are many nature inspired optimization algorithms have been introduced.In this study, a newly algorithm namely Grey Wolf Optimizer (GWO) is employed for gasoline price forecasting.The performance of GWO is compared against the results produced by Artificial Bee Colony (ABC) algorithm and Differential Evolution (DE) algorithm. …”
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    Article
  6. 6

    An Application of Grey Wolf Optimizer for Commodity Price Forecasting by Zuriani, Mustaffa, M. H., Sulaiman, Yuhani, Yusof

    Published 2015
    “…The performance of GWO is compared against the results produced by Artificial Bee Colony (ABC) algorithm and Differential Evolution (DE) algorithm. …”
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    Article
  7. 7

    Optimization of fed-batch fermentation processes using the Backtracking Search Algorithm by Mohd Zain, Mohamad Zihin, Kanesan, Jeevan, Kendall, Graham, Chuah, Joon Huang

    Published 2018
    “…However, the complexity of these processes requires an expert system that involves swarm intelligence-based metaheuristics such as Artificial Algae Algorithm (AAA), Artificial Bee Colony (ABC), Covariance Matrix Adaptation Evolution Strategy (CMAES) and Differential Evolution (DE) for simulation and optimization of the feeding trajectories. …”
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    Article
  8. 8

    Comparative Study of Economic Dispatch by Using Various Optimization Techniques by Hong, Mee Song, M. H., Sulaiman, Mohd Rusllim, Mohamed, Wong, Lo Ing

    Published 2014
    “…The optimization techniques used in this paper to do the comparison are Quadratic Programming (QP), Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO), Simulated Annealing (SA), Differential Evolution (DE) and Genetic Algorithm (GA). …”
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    Conference or Workshop Item
  9. 9

    A novel hybrid metaheuristic algorithm for short term load forecasting by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, Yuhanis, Yusof, Syafiq Fauzi, Kamarulzaman

    Published 2017
    “…Later, the efficiency of GWO-LSSVM is compared against three comparable hybrid algorithms namely LSSVM optimized by Artificial Bee Colony (ABC), Differential Evolution (DE) and Firefly Algorithms (FA). …”
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    Article
  10. 10

    Selective harmonic elimination in cascaded H-bridge multilevel inverter using hybrid APSO algorithm / Mudasir Ahmed by Mudasir , Ahmed

    Published 2019
    “…Simulation results show that, at the high-level inverter, the proposed algorithm can easily find the feasible solutions, however, GA, PSO, bee algorithm (BA), and differential evolution (DE) face the difficulty due to less exploration capability. …”
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    Thesis
  11. 11

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

    Published 2018
    “…In order to solve it, Bat Algorithm method is implement in to optimization method in fuzzy modeling for classification. …”
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    Undergraduates Project Papers
  12. 12

    Hybrid Metaheuristic Algorithm for Short Term Load Forecasting by Zuriani, Mustaffa, M. H., Sulaiman, Yuhanis, Yusof, Syafiq Fauzi, Kamarulzaman

    Published 2016
    “…Later, the efficiency of GWO-LSSVM is compared against three comparable hybrid algorithms namely LSSVM optimized by Artificial Bee Colony (ABC), Differential Evolution (DE) and Firefly Algorithms (FA). …”
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    Article
  13. 13

    Hybridization Of Deterministic And Metaheuristic Approaches In Global Optimization by Goh, Khang Wen

    Published 2019
    “…In the analysis of the literature, Artificial Bees Colony (ABC) Algorithm has been selected as the metaheuristic approach to be improved its capability and efficiency to solve the global optimization problems. …”
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    Thesis
  14. 14

    First Semester Computer Science Students’ Academic Performances Analysis by Using Data Mining Classification Algorithms by Azwa, Abdul Aziz, Fadhilah, Ahmad

    Published 2014
    “…The comparative analysis is also conducted to discover the best classification model for prediction. From the experiment, the models develop using Rule Based and Decision Tree algorithm shows the best result compared to the model develop from the Naïve Bayes algorithm. …”
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    Conference or Workshop Item
  15. 15

    Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

    Published 2019
    “…The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. Finally, both algorithms are validated against the findings in various literatures. …”
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    Thesis
  16. 16

    An Arabic hadith text classification model using convolutional neural network and support vector machine / Mohd Irwan Mazlin by Mazlin, Mohd Irwan

    Published 2022
    “…There are 6 different ways of designing the experiment to evaluate the result of the study, which are an experiment with the model using different stemming techniques, an experiment with the model using three different algorithms, the result analysis of confusion matric of three algorithms, experiment the model using different SVM kernel, experiment the model using unseen data, produce precision, recall, F1-measure and accuracy result of the model and parameter. …”
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    Thesis
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    Classification of gait parameters in stroke with peripheral neuropathy (PN) by using k-Nearest Neighbors (kNN) algorithm / N. Anang ...[et al.] by Anang, N., Jailani, R., Mustafah, N., Manaf, H.

    Published 2018
    “…The classification model developed has been successfully discriminate three different groups with 83.33% accuracy.…”
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    Article
  19. 19

    Symmetric Key Size for Different Level of Information Classification by Ibrahim, Subariah, Maarof, Mohd. Aizaini

    Published 2006
    “…By using this model, we then propose key sizes for different levels of information classification.…”
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    Conference or Workshop Item
  20. 20

    Feature selection and model selection algorithm using incremental mixed variable ant colony optimization for support vector machine classifier by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
    “…In order to enhance SVM performance, these problems must be solved simultaneously because error produced from the feature subset selection phase will affect the values of the SVM parameters and resulted in low classification accuracy.Most approaches related with solving SVM model selection problem will discretize the continuous value of SVM parameters which will influence its performance.Incremental Mixed Variable Ant Colony Optimization (IACOMV) has the ability to solve SVM model selection problem without discretising the continuous values and simultaneously solve the two problems.This paper presents an algorithm that integrates IACOMV and SVM.Ten datasets from UCI were used to evaluate the performance of the proposed algorithm.Results showed that the proposed algorithm can enhance the classification accuracy with small number of features.…”
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    Article