Search Results - time estimation ((sensor algorithm) OR (((bees algorithm) OR (based algorithm))))

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  1. 1

    Acoustic emission partial discharge localization in oil based on artificial bee colony by Lim, Zhi Yang, Azis, Norhafiz, Mohd Hashim, Ahmad Hafiz, Mohd Radzi, Mohd Amran, Norsahperi, Nor Mohd Haziq, Mohd Ariffin, Azrul

    Published 2025
    “…After 500 iterations, the optimal solution was the estimated PD location produced by ABC. Comparisons with the genetic algorithm (GA), particle swarm optimization (PSO) and bat algorithm (BA) revealed that the distance error, maximum deviation and computation time for AE PD localization based on ABC are the lowest. …”
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    Article
  2. 2

    Time Synchronization Using Distributed Observer Algorithm With Sliding Mode Control For Wireless Sensor Network by Yew, Tze Hui

    Published 2015
    “…The algorithm is known as Time Synchronization using Distributed Observer algorithm with Sliding mode control element (TSDOS).The main purpose of proposing TSDOS is to estimate a common global clock time by which all nodes within the WSN can use it for communication purpose. …”
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    Thesis
  3. 3

    Distance vector-hop range-free location algorithm for wireless sensor network by Zazali, Azyyati Adiah

    Published 2015
    “…The localization algorithms for sensor nodes can be classified into three categories; range-based, rangefree and hybrid. …”
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  4. 4

    Improved static and dynamic FBG sensor system for real-time monitoring of composite structures by Vorathin, Epin

    Published 2017
    “…Thus, the designation of this research study is to improve the current FBG based real-time monitoring system with the use of certain functions and algorithms, that are the instant mesh-grid function, voltage normalization algorithm, CC-LSL algorithm, and FFT function. …”
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    Thesis
  5. 5

    Inertial sensor-based instrumented cane for real-time walking cane kinematics estimation by Fernandez, Ibai Gorordo, Ahmad, Siti Anom, Wada, Chikamune

    Published 2020
    “…Based on inertial sensor data, the proposed system estimates the kinematics (contact phase and orientation) of the cane. …”
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  6. 6

    Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system by Nurnajmin Qasrina Ann, Ayop Azmi

    Published 2018
    “…Based on literature, stereo algorithm is already being implemented to solve the distance measurement problem. …”
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  7. 7

    Real time self-calibration algorithm of pressure sensor for robotic hand glove system by Almassri, Ahmed M. M.

    Published 2019
    “…This study investigates the use of a novel Proposed Self-Calibration Algorithm (PSCA) of multi pressure sensors in real time on robotic hand glove system. …”
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    Thesis
  8. 8

    The development of parameter estimation method for Chinese hamster ovary model using black widow optimization algorithm by Nurul Aimi Munirah, ., Muhammad Akmal, Remli, Noorlin, Mohd Ali, Hui, Wen Nies, Mohd Saberi, Mohamad, Khairul Nizar Syazwan, Wan Salihin Wong

    Published 2020
    “…The proposed algorithm has been compared with the other three famous algorithms, which are Particle Swarm Optimization (PSO), Differential Evolutionary (DE), and Bees Optimization Algorithm (BOA). …”
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    Article
  9. 9

    Railway wheelset parameter estimation using signals from lateral velocity sensor by Selamat, H., Alimin, A. J., Sam, Y.M.

    Published 2008
    “…A type of parameter estimation technique based on the linear integral filter (LIF) method, the least-absolute error with variable forgetting factor (LAE+VFF) estimation method, is proposed in this paper to estimate the railway wheelset parameters modelled as a time-varying continuous-time (C-T) system. …”
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  10. 10

    Novel chewing cycle approach for peak detection algorithm of chew count estimation by Selamat, Nur Asmiza, Md Ali, Sawal Hamid, Ismail, Ahmad Ghadafi, Ahmad, Siti Anom, Minhad, Khairun Nisa'

    Published 2025
    “…This work proposes a novel approach to chew count estimation using particle swarm optimization (PSO) combined with a peak detection algorithm. …”
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    Article
  11. 11

    Novel chewing cycle approach for peak detection algorithm of chew count estimation by Selamat, Nur Asmiza, Md Ali, Sawal Hamid, Ismail, Ahmad Ghadafi, Ahmad, Siti Anom, Minhad, Khairun Nisa’

    Published 2025
    “…This work proposes a novel approach to chew count estimation using particle swarm optimization (PSO) combined with a peak detection algorithm. …”
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  12. 12

    A hybrid algorithm of source localization based on hyperbolic technique in WSN by Kabir, H., Kanesan, J., Reza, A.W., Ramiah, H.

    Published 2014
    “…In this paper, a hybrid method combined with maximum likelihood (ML) and genetic algorithm (GA) are proposed to determine the instantaneous position of the moving source by estimating the position and velocity based on hyperbolic techniques (TDOA and FDOA). …”
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    Conference or Workshop Item
  13. 13

    SLOW DRIFT MOTIONS IDENTIFICATION OF FLOATING STRUCTURES USING TIME-VARYING INPUT -OUTPUT MODELS by YAZID, EDWAR

    Published 2015
    “…The first step is presenting the backward estimator and combined forward-backward estimator instead of the only forward estimator in the original input-output models; the second step is reformulating the input-output models into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the model coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Artificial Bee Colony (ABC) to form the PSO-KS, GA-KS and ABC-KS as estimation methods.…”
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  14. 14
  15. 15

    FBGs Real-Time Impact Damage Monitoring System of GFRP Beam Based on CC-LSL Algorithm by Vorathin, E., Zohari, Mohd Hafizi, Ghani, S.A. Che, Siregar, Januar Parlaungan, Lim, Kok Sing

    Published 2018
    “…Thus, in this paper, an in situ FBG sensor was embedded in a GFRP beam, providing an online real-time monitoring system and with the knowledge of cross-correlation linear source location (CC-LSL) algorithm, the impact location was capable of being determined in a split second. …”
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    Article
  16. 16

    GbLN-PSO Algorithm for indoor localization in wireless sensor network by M. Shahkhir, Mozamir, Rohani, Abu Bakar, Wan Isni Soffiah, Wan Din, Zalili, Musa

    Published 2020
    “…In this paper, we propose an indoor localization in WSN based on Global best Local Neighbourhood Particle Swarm Optimization (GbLN-PSO) algorithm. …”
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  17. 17

    Improvement of routing protocol in wireless sensor network for energy consumption to maximize network lifetime by A. Othman, Emad

    Published 2013
    “…The routing scheme and algorithm has the common objective of trying to extend the lifetime of the sensor network. …”
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    Thesis
  18. 18

    Spacecraft sun-pointing using coplanar solar panels data and magnetic field measurements by Mohammad Abdelrahman, Mohammad Ibraheem

    Published 2013
    “…The goal of this paper is to develop an algorithm for sun vector estimation without any explicit measurements from sun sensors. …”
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    Proceeding Paper
  19. 19

    FBGs Real-Time Impact Damage Monitoring System of GFRP Beam Based on CC-LSL Algorithm by Vorathin, E., Mohd Hafizi, Zohari, S. A., Che Ghani, Siregar, J. P., K. S., Lim

    Published 2018
    “…Thus, in this paper, an in situ FBG sensor was embedded in a GFRP beam, providing an online real-time monitoring system and with the knowledge of cross-correlation linear source location (CC-LSL) algorithm, the impact location was capable of being determined in a split second. …”
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    Article
  20. 20

    Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman Smoother adaptive filter by ., Edwar Yazid, Mohd Shahir Liew, Setyamartana Parman, Velluruzhati

    Published 2015
    “…This paper proposes three steps of improvements for identification of the nonlinear dynamic system, which exploits the concept of a state-space based time domain Volterra model. The first step is combining the forward and backward estimator in the original Volterra model; the second step is reformulating the Volterra model into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the kernel coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as particle swarm optimization (PSO), genetic algorithm (GA) and artificial bee colony (ABC). …”
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