Search Results - (( parameter estimation sensor algorithm ) OR ( pattern optimization based algorithm ))

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  1. 1
    A novel peak detection algorithm using particle swarm optimization for chew count estimation of a contactless chewing detection

    A novel peak detection algorithm using particle swarm optimization for chew count estimation of a contactless chewing detection by Selamat, Nur Asmiza, Md. Ali, Sawal Hamid, Minhad, Khairun Nisa’, Ahmad, Siti Anom, Sampe, Jahariah

    Published 2022
    “…First, the base of the algorithm is developed based on counting the peak of the chewing signal. …”
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  2. 2
    A novel peak detection algorithm using particle swarm optimization for chew count estimation of a contactless chewing detection

    A novel peak detection algorithm using particle swarm optimization for chew count estimation of a contactless chewing detection by Selamat, Nur Asmiza, Md. Ali, Sawal Hamid, Minhad, Khairun Nisa’, Ahmad, Siti Anom

    Published 2022
    “…First, the base of the algorithm is developed based on counting the peak of the chewing signal. …”
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  3. 3
    Railway wheelset parameter estimation using signals from lateral velocity sensor

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

    Published 2008
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  4. 4
    Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor / Muhammad Nasrul Hakim Adenan

    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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  5. 5
    Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor: article / Muhammad Nasrul Hakim Adenan and Maizatul Zolkapli

    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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  6. 6
    Performance study of direction of arrival (DOA) estimation algorithms for linear array antenna

    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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  7. 7
    Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman

    Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman by Che Osman, Siti Eshah

    Published 2019
    “…In this study, a pattern based using Particle Swarm Optimization (PSO) is proposed named as Hexagon PSO (HPSO). …”
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  8. 8
    Novel chewing cycle approach for peak detection algorithm of chew count estimation

    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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  9. 9
    Novel chewing cycle approach for peak detection algorithm of chew count estimation

    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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  10. 10
    Artificial intelligence techniques applied as estimator in chemical process systems - A literature survey

    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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  11. 11
    A Novel Approach to Estimate Diffuse Attenuation Coefficients for QuickBird Satellite Images: A Case Study at Kish Island, the Persian Gulf.

    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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  12. 12
    Sensorless Adaptive Fuzzy Logic Control Of Permanent Magnet Synchronous Motor

    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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  13. 13
    Sensor-less vector control using adaptive observer scheme for controlling the performance of the induction motor / Mazhar Hussain Abbasi

    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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  14. 14
    Interference reduction by null-forming optimization based MVDR technique using gravitational search algorithm

    Interference reduction by null-forming optimization based MVDR technique using gravitational search algorithm by Shahab, Suhail Najm, Ayib Rosdi, Zainun, Alabdraba, Waleed M. Sh., Nurul Hazlina, Noordin

    Published 2017
    “…In the present work, Gravitational Search Algorithm (GSA) is a new modern metaheuristic optimization technique used for optimizing the MVDR null-forming level by controlling the excitation weight coefficients in a linear antenna array radiation pattern synthesis. …”
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  15. 15
    Mussels wandering optimization algorithmn based training of artificial neural networks for pattern classification

    Mussels wandering optimization algorithmn based training of artificial neural networks for pattern classification by Abusnaina, Ahmed A., Abdullah, Rosni

    Published 2013
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  16. 16
    A hybrid algorithm of source localization based on hyperbolic technique in WSN

    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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  17. 17
    Improving explicit aspects extraction in sentiment analysis using optimized ruleset / Mohammad Ahmad Jomah Tubishat

    Improving explicit aspects extraction in sentiment analysis using optimized ruleset / Mohammad Ahmad Jomah Tubishat by Mohammad Ahmad, Jomah Tubishat

    Published 2019
    “…In addition, extraction rules including either pattern-based or dependency-based rules should be selected in a correct way to remove the irrelevant rules and minimize the extraction errors Thus, in this study, to select the most effective extraction rules, an improved version of Whale Optimization Algorithm (IWOA) is developed and applied to a full set of rules. …”
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  18. 18
    Performance optimization on axial-flux permanent magnet coreless generator using novel hybrid computational method based on genetic algorithm and pattern search / Lok Choon Long

    Performance optimization on axial-flux permanent magnet coreless generator using novel hybrid computational method based on genetic algorithm and pattern search / Lok Choon Long by Lok , Choon Long

    Published 2016
    “…Complex real-world problems can be solved by heuristic optimization efficiently. Improved hybrid optimization method using Pattern Search (PS) and Genetic Algorithm (GA) onto Axial-Flux Permanent Magnet (AFPM) Coreless generator is presented in this thesis, and the optimization is based on the popular multi-objective sizing equation. …”
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  19. 19
    Clustering ensemble learning method based on incremental genetic algorithms

    Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

    Published 2012
    “…In the first and second phases, a threshold fuzzy c-means clustering algorithm as a clusterer and a pattern ensemble learning method based on the incremental genetic-based algorithms are proposed respectively. …”
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  20. 20
    Modification Of Regression Models To Solve Heterogeneity Problem Using Seaweed Drying Data

    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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