Search Results - time estimation ((((method algorithm) OR (learning algorithm))) OR (based algorithm))

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  1. 1

    Kernel and multi-class classifiers for multi-floor wlan localisation by Abd Rahman, Mohd Amiruddin

    Published 2016
    “…The multi-class classification strategy is used to ensure quick estimation of the multi-class NN algorithms. All of the algorithms are later combined to provide device location estimation for multi-floor environment. …”
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    Thesis
  2. 2

    Adaptive beamforming algorithm based on Simulated Kalman Filter by Kelvin Lazarus, Lazarus

    Published 2017
    “…Zakwan, applies Opposition-Based Learning method to improve the exploration capabilities of SKF algorithm. …”
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    Thesis
  3. 3

    Lightweight spatial attentive network for vehicular visual odometry estimation in urban environments by Gadipudi, N., Elamvazuthi, I., Lu, C.-K., Paramasivam, S., Su, S.

    Published 2022
    “…However, current learning-based methods are computationally expensive and require a significant amount of time to estimate the pose from a video sequence. …”
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    Article
  4. 4

    Lightweight spatial attentive network for vehicular visual odometry estimation in urban environments by Gadipudi, N., Elamvazuthi, I., Lu, C.-K., Paramasivam, S., Su, S.

    Published 2022
    “…However, current learning-based methods are computationally expensive and require a significant amount of time to estimate the pose from a video sequence. …”
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    Article
  5. 5

    A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

    Published 2024
    “…The dissertation aims to develop an effectively decomposed time-series nongradient- based artificial intelligence model for forecasting a time-series regression machine learning task. …”
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    Thesis
  6. 6
  7. 7

    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

    Published 2023
    “…The first research objective is to develop a new deep learning algorithm by a hybrid of DNN and K-Means Clustering algorithms for estimating the Lorenz chaotic system. …”
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    Thesis
  8. 8

    RECURSIVE LEARNING ALGORITHMS ON RBF NETWORKS FOR NONLINEAR SYSTEM IDENTIFICATION by CATUR ANDRYANI, NUR AFNY

    Published 2010
    “…This thesis proposes derivative free learning, using finite difference, methods for fixed size RBF network in comparison to gradient based learning for the application of system identification. …”
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    Thesis
  9. 9
  10. 10

    Deep learning-based single-shot and real-time vehicle detection and ego-lane estimation by Abdul Matin, M. A. A., Ahmad Fakhri, A. S., Mohd Zaki, Hasan Firdaus, Zainal Abidin, Zulkifli, Mohd Mustafah, Y., Abd Rahman, H., Mahamud, N. H., Hanizam, S., Ahmad Rudin, N. S.

    Published 2020
    “…Our experimental results show that this method achieves real-time performance with test results of 88% total precision on the CULane dataset and 91% on our dataset for ego-lane estimation. …”
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    Article
  11. 11

    Feedforward neural network for solving particular fractional differential equations by Admon, Mohd Rashid

    Published 2024
    “…Then, a single hidden layer of FNN based on Chelyshkov polynomials with an extreme learning machine algorithm (SHLFNNCP-ELM) is constructed for solving FDEsC. …”
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    Thesis
  12. 12

    Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm by Manoharan P., Ravichandran S., Kavitha S., Tengku Hashim T.J., Alsoud A.R., Sin T.C.

    Published 2025
    “…The orthogonal learning mechanism improves the performance of the original GOOSE algorithm. …”
    Article
  13. 13

    Automatic database of robust neural network forecasting / Saadi Ahmad Kamaruddin, Nor Azura Md. Ghani and Norazan Mohamed Ramli by Ahmad Kamaruddin, Saadi, Md. Ghani, Nor Azura, Mohamed Ramli, Norazan

    Published 2014
    “…Most of the previous studies seek to improve the learning algorithm of backpropagation neural networks by adapting the M-estimators predominantly. …”
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    Book Section
  14. 14

    Enhancing the QoS performance for mobile station over LTE and WiMAX networks / Mhd Nour Hindia by Hindia, Mhd Nour

    Published 2015
    “…The selection is based on the user preferences since it uses a self-learning algorithm to determine triggers and handover thresholds dynamically. …”
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    Thesis
  15. 15

    High Accuracy Estimation Of Head Yaw Using Bounding Box Algorithm On A Vision Based System by Tarmizi, Aine Ilina

    Published 2020
    “…The percentage of accuracy of the yaw estimation using a bounding box algorithm is 92.4%. …”
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    Thesis
  16. 16

    Identification of continuous-time model of hammerstein system using modified multi-verse optimizer by Most. Julakha, Jahan Jui

    Published 2021
    “…his thesis implements a novel nature-inspired metaheuristic optimization algorithm, namely the modified Multi-Verse Optimizer (mMVO) algorithm, to identify the continuous-time model of Hammerstein system. …”
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    Thesis
  17. 17

    Software effort estimation using machine learning technique by Rahman, Mizanur, Roy, Partha Protim, Ali, Mohammad, Gonçalves, Teresa, Sarwar, Hasan

    Published 2023
    “…In order to better effectively evaluate predictions, this study recommends various machine learning algorithms for estimating, including k-nearest neighbor regression, support vector regression, and decision trees. …”
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    Article
  18. 18

    Real-Time Flood Inundation Map Generation Using Decision Tree Machine Learning Method: Case Study of Kelantan River Basins by Sidek L.M., Basri H., Marufuzzaman M., Deros A.M., Osman S., Hassan F.A.

    Published 2024
    “…Additionally, to predict the flood depth, a trained Decision Tree (DT)-based sorting algorithm is used in this method. This DT-based model takes 4 random rainfall data to train and predict the flood depth of the study area…”
    Book chapter
  19. 19

    An improved machine learning model of massive Floating Car Data (FCD) based on Fuzzy-MDL and LSTM-C for traffic speed estimation and prediction by Ahanin, Fatemeh

    Published 2023
    “…In the third method, a hybrid algorithm called LSTM-C-EST, which is a combination of Fuzzy-MDL and LSTM-C is proposed. …”
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    Thesis
  20. 20

    Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS by Hassan, S., Khanesar, M.A., Jaafar, J., Khosravi, A.

    Published 2017
    “…Since extreme learning machine is a non-iterative estimation procedure, it is faster than gradient-based algorithms which are iterative. …”
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    Article