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  1. 1
    Bee colony optimisation of the travelling salesman problem in light rail systems

    Bee colony optimisation of the travelling salesman problem in light rail systems by Wang, Chen, Leong, Kah Huo, Abdul-Rahman, Hamzah

    Published 2019
    “…The study reported in this paper aimed to identify the most efficient algorithm and develop a mathematical model based on artificial bee colony optimisation to solve this problem in light rail transit systems. …”
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  2. 2
    LSSVM parameters tuning with enhanced artificial bee colony

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

    Published 2014
    “…The proposed model was employed in predicting financial time series data and comparison is made against the standard Artificial Bee Colony (ABC) and Cross Validation (CV) technique.The simulation results assured the accuracy of parameter selection, thus proved the validity in improving the prediction accuracy with acceptable computational time.…”
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  3. 3
    Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics

    Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics by Mohammad Jarrah, Mu'ath Ibrahim

    Published 2018
    “…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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  4. 4
    Transfer learning in near infrared spectroscopy for stingless bee honey quality prediction across different months

    Transfer learning in near infrared spectroscopy for stingless bee honey quality prediction across different months by Suarin, Nur Aisyah Syafinaz, Chia, Kim Seng, Mohamad Fuzi, Siti Fatimah Zaharah

    Published 2024
    “…Thus, this study aims to evaluate the feasibility of homogenous transfer learning approaches to overcome data constraints in developing NIRS predictive models of stingless bee honey qualities across different months. …”
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  5. 5
    Enhanced ABD-LSSVM for energy fuel price prediction

    Enhanced ABD-LSSVM for energy fuel price prediction by Mustaffa, Zuriani, Yusof, Yuhanis, Kamaruddin, Siti Sakira

    Published 2013
    “…This paper presents an enhanced Artificial Bee Colony (eABC)based on Lévy Probability Distribution (LPD) and conventional mutation. …”
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  6. 6
    Optimizing Visual Surveillance Sensor Coverage Using Dynamic Programming

    Optimizing Visual Surveillance Sensor Coverage Using Dynamic Programming by Altahir, A.A., Asirvadam, V.S., Hamid, N.H.B., Sebastian, P., Saad, N.B., Ibrahim, R.B., Dass, S.C.

    Published 2017
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  7. 7
    Enhanced ABC-LSSVM For Energy Fuel Price Prediction

    Enhanced ABC-LSSVM For Energy Fuel Price Prediction by Mustaffa, Zuriani, Yusof, Yuhanis, Kamaruddin, Siti Sakira

    Published 2014
    “…To evaluate the effi ciency of the proposed model, crude oil prices data was employed as empirical data and a comparison against four approaches were conducted, which include standard ABC-LSSVM, Genetic Algorithm-LSSVM (GA-LSSVM), Cross Validation-LSSVM (CV-LSSVM), and conventional Back Propagation Neural Network (BPNN). …”
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  8. 8
    Developing Bus Tracking System that predicts the arrival times of public buses at Universiti Teknologi PETRONAS (UTP) bus stops.

    Developing Bus Tracking System that predicts the arrival times of public buses at Universiti Teknologi PETRONAS (UTP) bus stops. by Mohd Akhir, Norhasiah

    Published 2004
    “…The combination usage of the algorithm, AVL, GPS and SMS server, the information regarding the time arrival of the transport can easily being retrieve by users. …”
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  9. 9
    Modified anfis architecture with less computational complexities for classification problems

    Modified anfis architecture with less computational complexities for classification problems by Talpur, Noureen

    Published 2018
    “…The proposed ANFIS model is trained by one of the metaheuristics approach instead of standard two pass learning algorithm. …”
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  10. 10
    Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm

    Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

    Published 2025
    “…In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”
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  11. 11
    Adaptive intelligence job online scheduling within dynamic grid environment based on gridsim

    Adaptive intelligence job online scheduling within dynamic grid environment based on gridsim by Lorpunmanee, Siriluck, Md. Sap, Mohd. Noor, Abdullah, Abdul Hanan

    Published 2008
    “…Moreover, both dynamic and static information are handled by the solution. In static case, the resource information such as a number of CPUs of a machine, CPU speed, a number machine in the grid system is significantly known in advance while dynamic information like the arrival jobs that are submitted to the system any time during simulation. …”
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  12. 12
    Job online scheduling within dynamic grid environment

    Job online scheduling within dynamic grid environment by Lorpunmanee, Siriluck, Md. Sap, Mohd. Noor, Abdullah, Abdul Hanan

    Published 2008
    “…While, Tabu algorithm is used to adjust performance of grid system because online jobs are submitted to grid system from time to time. …”
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  13. 13
    SVM for network anomaly detection using ACO feature subset

    SVM for network anomaly detection using ACO feature subset by Mehmood, T., Rais, H.B.M.

    Published 2016
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  14. 14
    A semi greedy soft real-time multiprocessor scheduling algorithm

    A semi greedy soft real-time multiprocessor scheduling algorithm by Alhussian, Hitham, Zakaria, Mohd Nordin, Hussin, Fawnizu Azmadi

    Published 2014
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  15. 15
    A Non-preemptive Utility Accrual Scheduling Algorithm in iAdaptive Real Time System

    A Non-preemptive Utility Accrual Scheduling Algorithm in iAdaptive Real Time System by Ahmad, Idawaty, Othman, Muhammad Fauzan

    Published 2008
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  16. 16
    Privacy in medical emergency system: cryptographic and security aspects

    Privacy in medical emergency system: cryptographic and security aspects by Hameed, Shihab A., Yuchoch, Habib, Al-Khateeb, Wajdi Fawzi Mohammed

    Published 2010
    “…This discovery suggests that selecting appropriated algorithms for data encryption in different ranges of data size affects processing time supporting Medical Emergency System.…”
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  17. 17
    A preemptive utility accrual scheduling algorithm in adaptive real time system.

    A preemptive utility accrual scheduling algorithm in adaptive real time system. by Ahmad, Idawaty, Subramaniam, Shamala, Othman, Mohamed, Othman, Muhammad Fauzan

    Published 2008
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  18. 18
    Improving utility accrual scheduling algorithm for adaptive real-time system

    Improving utility accrual scheduling algorithm for adaptive real-time system by Ahmad, Idawaty, Othman, Mohamed, Ahmad Zukarnain, Zuriati, Othman, Muhammad Fauzan

    Published 2008
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  19. 19
    CPU scheduling with a round Robin algorithm based on an effective time slice

    CPU scheduling with a round Robin algorithm based on an effective time slice by Tajwar, Mohammad M., Pathan, Md. Nuruddin, Hussaini, Latifa, Abubakar, Adamu

    Published 2017
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  20. 20
    Boyer-Moore horspool algorithm used in content management system of data fast searching

    Boyer-Moore horspool algorithm used in content management system of data fast searching by Chan, Chung Hoong, M. A., Ameedeen

    Published 2017
    “…After a deep view on few fast searching algorithm as Boyer-Moore algorithm, Boyer-Moore Horspool algorithm, Brute-Force Algorithm, Knuth-Morris-Pratt algorithm and Rabin-Karp algorithm, this research paper chooses Boyer-Moore Horspool algorithm to used in the content management system in term of data Fast Searching. …”
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