Search Results - (( java application bees algorithm ) OR ( parameter virtualization learning algorithm ))

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  1. 1

    Enhancing hyperparameters of LSTM network models through genetic algorithm for virtual learning environment prediction by Ismanto, Edi, Ab Ghani, Hadhrami, Md Saleh, Nurul Izrin

    Published 2025
    “…In today's technology-driven era, innovative methods for predicting behaviors and patterns are crucial. Virtual Learning Environments (VLEs) represent a rich domain for exploration due to their abundant data and potential for enhancing learning experiences. …”
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    Article
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    Machine learning model to predict the contact of angle using mineralogy, TOC and process parameters in shale by Ameenuddin Irfan, S., Fadhli, M.Z., Padmanabhan, E.

    Published 2021
    “…A machine learning is needed to predict the contact angle in the shale using the process parameters and TOC and Minerology of the shale. …”
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    Artificial neural networks based optimization techniques: A review by Abdolrasol M.G.M., Suhail Hussain S.M., Ustun T.S., Sarker M.R., Hannan M.A., Mohamed R., Ali J.A., Mekhilef S., Milad A.

    Published 2023
    “…This paper emphasizes enhancing the neural network via optimization algorithms by manipulating its tuned parameters or training parameters to obtain the best structure network pattern to dissolve the problems in the best way. …”
    Review
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    A dataset for emotion recognition using virtual reality and EEG (DER-VREEG): Emotional state classification using low-cost wearable VR-EEG headsets by Nazmi Sofian Suhaimi, James Mountstephens, Teo, Jason Tze Wi

    Published 2022
    “…Finally, we evaluate the emotion recognition system by using popular machine learning algorithms and compare them for both intra-subject and inter-subject classification. …”
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    Article
  16. 16

    PATCH-IQ: A Patch Based Learning Framework For Blind Image Quality Assessment by Abdul Manap, Redzuan, Ling, Shao, Frangi, Alejandro Federico

    Published 2017
    “…However, this approach requires an intensive training phase to optimise the regression parameters. In this paper, we overcome this limitation by proposing an alternative BIQA model that predicts image quality using nearest neighbour methods which have virtually zero training cost. …”
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    Article
  17. 17

    REGION-BASED ADAPTIVE DISTRIBUTED VIDEO CODING CODEC by ABDELRAHMAN ELAMIN, ABDELRAHMAN ELAMIN

    Published 2011
    “…The partitioning allows allocation of appropriate DVC coding parameters (virtual channel, rate, and quantizer) to each region. …”
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    Thesis
  18. 18

    Hybrid indoor positioning utilizing multipath- assisted fingerprint and geometric estimation for single base station systems by Manap, Zahariah

    Published 2025
    “…The key attributes that establish the classification learning sessions are the channel parameters extracted from the ray tracing generated multipath signals. …”
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    Thesis
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    Development of compound clustering techniques using hybrid soft-computing algorithms by Salim, Naomie, Shamsuddin, Siti Mariyam, Salleh @ Sallehuddin, Roselina, Alwee, Razana

    Published 2006
    “…With the advent of combinatorial chemistry, a vast number of compounds can be available either physically or virtually, which can make screening all of them infeasible in terms of time and cost. …”
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    Monograph
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    Three-dimensional craniometrics identification model and cephalic index classification of Malaysian sub-adults: A multi-slice computed tomography study / Sharifah Nabilah Syed Mohd... by Sharifah Nabilah , Syed Mohd Hamdan

    Published 2024
    “…MIMICS software version 21.0 (Materialise, Leuven, Belgium) was used to construct 3D models and plane-to-plane (PTP) protocol was utilised to measure 14 selected craniometric parameters. Discriminant function analysis (DFA), binary logistic regression (BLR), and several machine learning (ML) algorithms (random forest (RF), support vector machines (SVM), and linear discriminant analysis (LDA)) were used to statistically analyse the data. …”
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    Thesis