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  1. 1
    Clustering natural language morphemes from EEG signals using the Artificial Bee Colony algorithm

    Clustering natural language morphemes from EEG signals using the Artificial Bee Colony algorithm by Sulaiman, Suriani, Ahmed Yahya, Saba, Mohd Shukor, Nur Sakinah, Ismail , Amelia Ritahani, Zaahirah, Qazi, Yaacob, Hamwira, Abdul Rahman, Abdul Wahab, Dzulkifli, Mariam Adawiah

    Published 2015
    “…This study aims at analyzing EEG signals for the purpose of clustering natural language morphemes using the Artificial Bee Colony (ABC) algorithm. Using as input the features extracted from EEG signals during morphological priming tasks, our experimental results indicate that applying the ABC algorithm on EEG datasets to cluster Malay morphemes produces promising results.…”
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  2. 2
    Enhanced weight-optimized recurrent neural networks based on sine cosine algorithm for wave height prediction

    Enhanced weight-optimized recurrent neural networks based on sine cosine algorithm for wave height prediction by Alqushaibi, A., Abdulkadir, S.J., Rais, H.M., Al-Tashi, Q., Ragab, M.G., Alhussian, H.

    Published 2021
    “…Therefore, the wind plays an essential role in the oceanic atmosphere and contributes to the formation of waves. This paper proposes an enhanced weight-optimized neural network based on Sine Cosine Algorithm (SCA) to accurately predict the wave height. …”
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  3. 3
    Clustering natural language morphemes from EEG signals using the Artificial Bee Colony algorithm

    Clustering natural language morphemes from EEG signals using the Artificial Bee Colony algorithm by Sulaiman, Suriani, Ahmed Yahya, Saba, Mohd Shukor, Nur Sakinah, Ismail , Amelia Ritahani, Zaahirah, Qazi, Yaacob, Hamwira Sakti, Abdul Rahman, Abdul Wahab, Dzulkifli, Mariam Adawiah

    Published 2015
    “…This study aims at analyzing EEG signals for the purpose of clustering natural language morphemes using the Artificial Bee Colony (ABC) algorithm. Using as input the features extracted from EEG signals during morphological priming tasks, our experimental results indicate that applying the ABC algorithm on EEG datasets to cluster Malay morphemes produces promising results.…”
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  4. 4
    Intelligent road recognition system for automous vehicle

    Intelligent road recognition system for automous vehicle by Soon, Adrian Bee Toing

    Published 2013
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    Thesis
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  5. 5
    An inclusive multiple model for predicting total sediment transport rate in the presence of coastal vegetation cover based on optimized kernel extreme learning models

    An inclusive multiple model for predicting total sediment transport rate in the presence of coastal vegetation cover based on optimized kernel extreme learning models by Jalil-Masir H., Fattahi R., Ghanbari-Adivi E., Asadi Aghbolaghi M., Ehteram M., Ahmed A.N., El-Shafie A.

    Published 2023
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  6. 6
    A generalized laser simulator algorithm for optimal path planning in constraints environment

    A generalized laser simulator algorithm for optimal path planning in constraints environment by Aisha, Muhammad

    Published 2022
    “…The mean path cost generated by the LS algorithm, on the other hand, is 14% higher than that generated by the PRM. …”
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  7. 7
    Data normalization techniques in swarm-based forecasting models for energy commodity spot price

    Data normalization techniques in swarm-based forecasting models for energy commodity spot price by Yusof, Yuhanis, Mustaffa, Zuriani, Kamaruddin, Siti Sakira

    Published 2014
    “…Data mining is a fundamental technique in identifying patterns from large data sets.The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical.Prior to that, data are consolidated so that the resulting mining process may be more efficient.This study investigates the effect of different data normalization techniques.which are Min-max, Z-score and decimal scaling, on Swarm-based forecasting models.Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC).Forecasting models are later developed to predict the daily spot price of crude oil and gasoline.Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max.Nevertheless, the GWO is more superior than ABC as its model generates the highest accuracy for both crude oil and gasoline price.Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.…”
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  8. 8
    Artificial Bee Colony With Differential Evolution Algorithm For Feature Extraction And Selection Of Mass Spectrometry Data

    Artificial Bee Colony With Differential Evolution Algorithm For Feature Extraction And Selection Of Mass Spectrometry Data by Mohamed Yusoff, Syarifah Adilah

    Published 2016
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  9. 9
    Rock brittleness prediction through two optimization algorithms namely particle swarm optimization and imperialism competitive algorithm

    Rock brittleness prediction through two optimization algorithms namely particle swarm optimization and imperialism competitive algorithm by Hussain, Azham, Surendar, A., Clementking, A., Kanagarajan, Sujith, Ilyashenko, Lubov K.

    Published 2018
    “…The main goal of this research work is to propose the novel practical models to predict the BI through particle swarm optimization (PSO) and imperialism competitive algorithm (ICA). …”
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  10. 10
    Interferometric array planning using division algorithm for radio astronomy applications

    Interferometric array planning using division algorithm for radio astronomy applications by Kiehbadroudinezhad, Shahideh

    Published 2017
    “…In the second scheme, a genetic algorithm is developed, in order to optimize a correlator array of antennas by using Genetic Algorithm (GA). …”
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  11. 11
    Hydraulic characterization of PVC-O pipes by means of transient tests

    Hydraulic characterization of PVC-O pipes by means of transient tests by Ghazali, M. F., Nizwan, Che Ku Eddy, Ismail, Nurazima, Sani, M. S.M., Yusof, Mohd Fadhlan M., Mohamed, Zamri

    Published 2019
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  12. 12
    Development of a State-Space Observer for Active Noise Control Systems

    Development of a State-Space Observer for Active Noise Control Systems by Muhssin, Mazin T.

    Published 2009
    “…The secondary path of the ANC system is modeled by using the LMS algorithm to complete the design of the Filtered-X Least Mean Square (FXLMS) controller. …”
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  13. 13
    Optimization of flood inundation simulation using multi-resolution Digital elevation model

    Optimization of flood inundation simulation using multi-resolution Digital elevation model by Abdul Kadir, Muhammad Azraie

    Published 2022
    “…This is due to the limitation of diffusive wave algorithm, 2-dimensional model and effect of grid configuration. …”
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  14. 14
    Characterization of oil palm fruitlets using artificial neural network

    Characterization of oil palm fruitlets using artificial neural network by Olukayode, Ojo Adedayo

    Published 2014
    “…The results also showed that contrary to the widely reported gap between the accuracy of the LM algorithm and other feed forward neural network training algorithms, the RP trained network performed as good as that of the LM algorithm for the range of data considered. …”
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  15. 15
    Triple nonlinear hyperbolic PID with static friction compensation for precise positioning of a servo pneumatic actuator

    Triple nonlinear hyperbolic PID with static friction compensation for precise positioning of a servo pneumatic actuator by Abdullah, Lokman, Kamaludin, Khairun Najmi, Syed Salim, Syed Najib, Rafan, Nur Aidawaty, Jamaludin, Zamberi, Rahmat, Mohd Fua'ad, Ramanathan, Rprakash

    Published 2023
    “…Although the FSS model caters to friction compensation, optimizing the FSS parameter by applying artificial intelligence, such as Neural Networks (NN) and Genetic Algorithm (GA), will increase the friction modeling‘s accuracy, and improve the compensation…”
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