Search Results - (( using optimization means algorithm ) OR ( parameter estimation sensor algorithm ))

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  1. 1

    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
    “…The peak detection algorithm identifies key signal features, while PSO optimizes the peak prominence and width parameters to minimize the mean absolute error (MAE) in chew count estimation. …”
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    Article
  2. 2

    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
    “…The peak detection algorithm identifies key signal features, while PSO optimizes the peak prominence and width parameters to minimize the mean absolute error (MAE) in chew count estimation. …”
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    Article
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    A contactless computer vision system for underwater walking and jogging gait analysis using YOLO-pose and Multi-CNN BiLSTM architecture by Cheng, Tong Bao, Khairuddin, Uswah

    Published 2025
    “…A comparison of hyperparameter optimization algorithms was conducted, with the combination of multivariate tree-structured Parzen estimators (MultiTPE) and Hyperband identified as the optimal approach. …”
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    Article
  7. 7

    Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor / Muhammad Nasrul Hakim Adenan by Adenan, Muhammad Nasrul Hakim

    Published 2013
    “…The algorithm will be developed in MATLAB. The objective of this project is to develop ANN model for ISFET sensor that able to estimate the main ion in mixed solution by learning the pattern of the input and output of the sensor. …”
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    Thesis
  8. 8

    Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor: article / Muhammad Nasrul Hakim Adenan and Maizatul Zolkapli by Hakim Adenan, Muhammad Nasrul, Zolkapli, Maizatul

    Published 2013
    “…The algorithm will be developed in MATLAB. The objective of this project is to develop ANN model for ISFET sensor that able to estimate the main ion in mixed solution by learning the pattern of the input and output of the sensor. …”
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    Article
  9. 9

    A comprehensive analysis of surface electromyography for control of lower limb exoskeleton by Abdelhakim, Deboucha

    Published 2016
    “…The developed algorithm for the crosstalk recordings detection shows ability in determining the presence of the overlapped measurements period. …”
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    Thesis
  10. 10

    Performance study of direction of arrival (DOA) estimation algorithms for linear array antenna by Islam, Md. Rafiqul, Adam, Ibrahim A. H.

    Published 2009
    “…The analysis is based on linear array antenna and the calculation of the pseudospectra function of the estimation algorithms. Matlab is used for simulating the algorithms.…”
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    Proceeding Paper
  11. 11

    Artificial intelligence techniques applied as estimator in chemical process systems - A literature survey by Ali, J.M., Hussain, Mohd Azlan, Tade, M.O., Zhang, J.

    Published 2015
    “…The versatility of Artificial Intelligence (AI) in process systems is not restricted to modelling and control,only, but also as estimators to estimate the unmeasured parameters as an alternative to the conventional observers and hardware sensors. …”
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    Article
  12. 12

    A Novel Approach to Estimate Diffuse Attenuation Coefficients for QuickBird Satellite Images: A Case Study at Kish Island, the Persian Gulf. by Pradhan, Biswajeet, Mohd Shafri, Helmi Zulhaidi, Mansor, Shattri, Kabiri, Keivan, Samim-Namin, Kaveh

    Published 2013
    “…Since the aforementioned algorithm has been developed for other types of sensors, an approach using weighted mean value of parameters for SeaWiFS, MERIS, VIIRS, and OCTS sensors were employed to estimate parameter values for QuickBird image. …”
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    Article
  13. 13

    Sensorless Adaptive Fuzzy Logic Control Of Permanent Magnet Synchronous Motor by Hafz Nour, Mutasim Ibrahim

    Published 2008
    “…This work also presents the estimation of the rotor position, which works effectively with nearly zero estimation error over wide speed range, to replace the electrometrical rotor position sensor. …”
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    Thesis
  14. 14

    Sensor-less vector control using adaptive observer scheme for controlling the performance of the induction motor / Mazhar Hussain Abbasi by Mazhar, Hussain Abbasi

    Published 2013
    “…Internal parameters are used, for example, feed-forward compensator of current controller and parameters of observer model in sensor less position. …”
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    Thesis
  15. 15

    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
  16. 16

    Modification Of Regression Models To Solve Heterogeneity Problem Using Seaweed Drying Data by Joshua, Ibidoja Olayemi

    Published 2023
    “…After the heterogeneity parameters were excluded from the model, the support vector machine with the MM estimator showed that better significant results were obtained with 2.09% outliers. …”
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    Thesis
  17. 17

    Hybrid fuzzy-sliding mode observer design for estimation and advanced control of an ethylene polymerization process / Jarinah Mohd Ali by Jarinah , Mohd Ali

    Published 2017
    “…Observers are computational algorithms designed to estimate unmeasured state variables due to the lack of appropriate estimating devices or to replace the high-priced sensors in a plant. …”
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    Thesis
  18. 18

    Optimized clustering with modified K-means algorithm by Alibuhtto, Mohamed Cassim

    Published 2021
    “…Clustering technique is able to find hidden patterns and to extract useful information from huge data. Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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    Thesis
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    A near-optimal centroids initialization in K-means algorithm using bees algorithm by Mahmuddin, Massudi, Yusof, Yuhanis

    Published 2009
    “…The K-mean algorithm is one of the popular clustering techniques.The algorithm requires user to state and initialize centroid values of each group in advance. …”
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    Conference or Workshop Item