Search Results - (( wave optimization sensor algorithm ) OR ( pattern extraction bees algorithm ))*

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  1. 1

    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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    Proceeding Paper
  2. 2

    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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    Book Chapter
  3. 3

    A miniature stub-loaded antenna optimized at VHF band for FSR sensor application / Hasrul Hisyam Harun by Harun, Hasrul Hisyam

    Published 2014
    “…This article demonstrated a miniature monopole antenna optimization at VHF band (30-300MHz) for FSR sensor application. …”
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    Thesis
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    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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    Conference or Workshop Item
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    Machine learning in botda fibre sensor for distributed temperature measurement by Nur Dalilla binti Nordin

    Published 2023
    “…The results obtained in these experiments would provide some overview in deploying machine learning algorithm for characterizing the Brillouin-based fibre sensor signals.…”
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  9. 9

    Efficient and scalable ant colony optimization based WSN routing protocol for IoT by Sharmin, Afsah, Anwar, Farhat, Motakabber, S. M. A.

    Published 2020
    “…For this reason, many intelligent systems have been utilized to design routing algorithms to handle the network's dynamic state. In this paper, an ant colony optimization (ACO) based WSN routing algorithm for IoT has been proposed and analyzed to enhance scalability, to accommodate node mobility and to minimize initialization delay for time critical applications in the context of IoT to find the optimal path of data transmission, improvising efficient IoT communications. …”
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    Article
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    Feasibility study on utilization of stub loaded miniature monopole antenna for forwards scattering micro-radar (FSR) network project: article / Hamid Salim by Salim, Hamid

    Published 2013
    “…The result obtained from both execution of Genetic Algorithm (GA) optimization and Parameter Sweep analysisis presented and conclude by future work recommendations for the continuity of this research.…”
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    Article
  12. 12

    Feasibility study on utilization of stub loaded miniature monopole antenna for forwards scattering micro-radar (FSR) network project / Hamid Salim by Salim, Hamid

    Published 2013
    “…The result obtained from both execution of Genetic Algorithm (GA) optimization and Parameter Sweep analysisis presented and conclude by future work recommendations for the continuity of this research.…”
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    Thesis
  13. 13

    Bayesian Network Classifiers for Damage Detection in Engineering Material by Mohamed Addin, Addin Osman

    Published 2007
    “…To validate the classi¯ers and the proposed algorithm, two data sets were used, the ¯rst set represents voltage amplitudes of Lamb-waves produced and col- lected by sensors and actuators mounted on the surface of laminates contain di®erent arti¯cial damages. …”
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    Thesis