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  1. 1

    Lévy mutation in artificial bee colony algorithm for gasoline price prediction by Mustaffa, Zuriani, Yusof, Yuhanis

    Published 2012
    “…In this paper, a mutation strategy that is based on Lévy Probabily Distribution is introduced in Artificial Bee Colony algorithm. The purpose is to better exploit promising solutions found by the bees.Such an approach is used to improve the performance of the original ABC in optimizing Least Squares Support Vector Machine hyper parameters.From the conducted experiment, the proposed lvABC shows encouraging results in optimizing parameters of interest.The proposed.lvABC-LSSVM has outperformed existing prediction model, Backpropogation Neural Network (BPNN), in predicting gasoline price.…”
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  2. 2

    Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction by Zuriani, Mustaffa

    Published 2014
    “…This study proposed a hybrid algorithm, based on Artificial Bee Colony (ABC) and LSSVM, that consists of three algorithms; ABC-LSSVM, lvABC-LSSVM and cmABC-LSSVM. …”
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    Thesis
  3. 3

    Enhanced artificial bee colony for training least squares support vector machines in commodity price forecasting by Mustaffa, Zuriani, Yusof, Yuhanis, Kamaruddin, Siti Sakira

    Published 2014
    “…The importance of optimizing machine learning control parameters has motivated researchers to investigate for proficient optimization techniques.In this study, a Swarm Intelligence approach, namely artificial bee colony (ABC) is utilized to optimize parameters of least squares support vector machines.Considering critical issues such as enriching the searching strategy and preventing over fitting, two modifications to the original ABC are introduced. …”
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    Article
  4. 4

    Application of LSSVM by ABC in energy commodity price forecasting by Mustaffa, Zuriani, Yusof, Yuhanis, Kamaruddin, Siti Sakira

    Published 2014
    “…The importance of the hyper parameters selection for a kernel-based algorithm, viz.Least Squares Support Vector Machines (LSSVM) has been a critical concern in literature.In order to meet the requirement, this work utilizes a variant of Artificial Bee Colony (known as mABC) for hyper parameters selection of LSSVM.The mABC contributes in the exploitation process of the artificial bees and is based on Levy mutation.Realized in crude oil price forecasting, the performance of mABC-LSSVM is guided based on Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSPE) and compared against the standard ABC-LSSVM and LSSVM optimized by Genetic Algorithm. …”
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  5. 5

    Multiobjective optimization using weighted sum Artificial Bee Colony algorithm for Load Frequency Control by Naidu, K., Mokhlis, Hazlie, Bakar, Ab Halim Abu

    Published 2014
    “…This paper presents the implementation of multiobjective based optimization of Artificial Bee Colony (ABC) algorithm for Load Frequency Control (LFC) on a two area interconnected reheat thermal power system. …”
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    Article
  6. 6

    A Hybrid ANFIS-ABC Based MPPT Controller for PV System with Anti-Islanding Grid Protection: Experimental Realization by Padmanaban S., Priyadarshi N., Bhaskar M.S., Holm-Nielsen J.B., Ramachandaramurthy V.K., Hossain E.

    Published 2023
    “…Controllers; Distributed power generation; Electric inverters; Electric power system protection; Fuzzy control; Fuzzy inference; Fuzzy logic; Fuzzy neural networks; Fuzzy systems; Inference engines; Maximum power point trackers; Mean square error; Membership functions; Optimization; Photovoltaic cells; Adaptive neuro-fuzzy inference system; Anti-islanding protection; Artificial bee colony algorithms (ABC); Experimental realizations; Experimental validations; Fuzzy-logic control; Photovoltaic systems; Root mean square errors; Electric power system control…”
    Article
  7. 7

    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
  8. 8

    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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    Final Year Project
  9. 9

    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
  10. 10

    Artificial Bee Colony-based satellite image contrast and brightness enhancement technique using DWT-SVD by Bhandari, A.K., Soni, V., Kumar, A., Singh, G.K.

    Published 2014
    “…The proposed technique is based on the Artificial Bee Colony (ABC) algorithm using Discrete Wavelet Transform and Singular Value Decomposition (DWT-SVD). …”
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    Article
  11. 11

    LS-SVM Hyper-parameters Optimization Based on GWO Algorithm for Time Series Forecasting by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, M. N. M., Kahar

    Published 2015
    “…In this study, a new metaheuristic algorithm, viz., Grey Wolf Optimizer (GWO), is employed to optimize the parameters of interest. …”
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  12. 12

    Structural optimization of 4-DOF agricultural robot arm by Nurul Emylia Natasya Ahmad Zakey, Mohd Hairi Mohd Zaman, Mohd Faisal Ibrahim

    Published 2024
    “…This study studies various optimization algorithms to compare the performance of algorithms that can achieve the optimal length with minimum errors. …”
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    Article
  13. 13

    LSSVM parameters tuning with enhanced artificial bee colony by Mustaffa, Zuriani, Yusof, Yuhanis

    Published 2014
    “…To guarantee its convincing performance, it is crucial to select an appropriate technique in order to obtain the optimized hyper-parameters of LSSVM algorithm.In this paper, an Enhanced Artificial Bee Colony (eABC) is used to obtain the ideal value of LSSVM’s hyper parameters, which are regularization parameter, γ and kernel parameter, σ2.Later, LSSVM is used as the prediction model. …”
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    Article
  14. 14

    Gasoline price forecasting: An application of LSSVM with improved ABC by Mustaffa, Zuriani, Yusof, Yuhanis, Kamaruddin, Siti Sakira

    Published 2014
    “…Optimizing the hyper-parameters of Least Squares Support Vector Machines (LSSVM) is crucial as it will directly influence the predictive power of the algorithm.To tackle such issue, this study proposes an improved Artificial Bee Colony (IABC) algorithm which is based on conventional mutation.The IABC serves as an optimizer for LSSVM.Realized in gasoline price forecasting, the performance is guided based on Mean Absolute Percentage Error (MAPE) and Root Mean Square Percentage Error (RMSPE).The conducted simulation results show that, the proposed IABCLSSVM outperforms the results produced by ABC-LSSVM and also the Back Propagation Neural Network.…”
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  15. 15

    Effectiveness of Nature-Inspired Algorithms using ANFIS for Blade Design Optimization and Wind Turbine Efficiency by Sarkar, Md Rasel, Julai, Sabariah, Chong, Wen Tong, Toha, Siti Fauziah

    Published 2019
    “…In this paper, nature-inspired algorithms, e.g., ant colony optimization (ACO), artificial bee colony (ABC), and particle swarm optimization (PSO) are used to search for the blade parameters that can give the maximum value of Cp for HAWT. …”
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    Article
  16. 16

    Provider independent cryptographic tools by Ibrahim, Subariah, Salleh, Mazleena, Abdul Aziz, Shah Rizan

    Published 2003
    “…The library is implemented by using Java cryptographic service provider framework that conforms to Java Cryptographic Architecture (JCA) and Java Cryptographic Extension (JCE). …”
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    Monograph
  17. 17

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
    “…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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    Thesis
  18. 18

    An application of hybrid swarm intelligence algorithms for dengue outbreak prediction by Mustaffa, Zuriani, Sulaiman, Mohd Herwan, Mohsin, M. F. M., Yusof, Y., Ernawan, Ferda, Rosli, K. A. M.

    Published 2019
    “…Concerning this matter, this study presents an application of hybrid Swarm Intelligence (SI) algorithms for a dengue outbreak prediction. For simulation purposes, a monthly dengue cases time series data in the area of Indonesia were employed, which are fed to four hybrid SI algorithms, namely Moth Flame Optimization (MFO), Grey Wolf Optimizer (GWO), Firefly Algorithm (FA) and Artificial Bee Colony (ABC) algorithm. …”
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  19. 19

    Effectiveness of nature-inspired algorithms using ANFIS for blade design optimization and wind turbine efficiency by Sarkar, Md. Rasel, Julai, Sabariah, Chong, Wen Tong, Toha @ Tohara, Siti Fauziah

    Published 2019
    “…In this paper, nature-inspired algorithms, e.g., ant colony optimization (ACO), artificial bee colony (ABC), and particle swarm optimization (PSO) are used to search for the blade parameters that can give the maximum value of Cp for HAWT. …”
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    Article
  20. 20

    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

    Published 2008
    “…The prototype system, known as Java Plagiarism Detection System (JPDS) implements the Greedy-String-Tiling algorithm to detect similarities among tokens in a Java source code files. …”
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    Thesis