Search Results - parameter estimation ((((learning algorithm) OR (sensor algorithm))) OR (max algorithm))

Refine Results
  1. 1

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

    Published 2013
    “…The ANN model performance can be optimized by altering certain parameters in the learning algorithm. The results show that the model is able to predict with 97% accuracy and has strong and precise estimation ability with R-factor of 91.55%.…”
    Get full text
    Get full text
    Thesis
  2. 2

    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 ANN model performance can be optimized by altering certain parameters in the learning algorithm. The results show that the model is able to predict with 97% accuracy and has strong and precise estimation ability with R-factor of 91.55%.…”
    Get full text
    Get full text
    Article
  3. 3

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

    Published 2016
    “…In this work, two AP selection algorithms are proposed which are Max Kernel and Kernel Logistic Discriminant that implement the knowledge of kernel density estimate and logistic regression machine learning classification. …”
    Get full text
    Get full text
    Thesis
  4. 4

    Electric vehicle battery state of charge estimation using metaheuristic-optimized CatBoost algorithms by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Ahmad Salihin, Samsudin, Amir Izzani, Mohamed, Mohd Mawardi, Saari

    Published 2025
    “…A comprehensive data preprocessing pipeline was implemented, including missing value treatment, outlier removal, and feature normalization using Min-Max scaling. Three distinct metaheuristic algorithms were investigated: Barnacles Mating Optimizer (BMO), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Whale Optimization Algorithm (WOA), each integrated with CatBoost to optimize critical parameters including learning rate, tree depth, regularization, and bagging temperature. …”
    Get full text
    Get full text
    Get full text
    Article
  5. 5

    Real-Time State of Charge Estimation of Lithium-Ion Batteries Using Optimized Random Forest Regression Algorithm by Hossain Lipu M.S., Hannan M.A., Hussain A., Ansari S., Rahman S.A., Saad M.H.M., Muttaqi K.M.

    Published 2024
    “…This paper presents an improved machine learning approach for the accurate and robust state of charge (SOC) in electric vehicle (EV) batteries using differential search optimized random forest regression (RFR) algorithm. …”
    Article
  6. 6
  7. 7

    Machine learning for mapping and forecasting poverty in North Sumatera: a datadriven approach by Marpaung, Faridawaty, Ramadhani, Fanny, Dinata, Dewan

    Published 2024
    “…The best model was created using the grid search cross-validation, while the best prediction results were created using the RF algorithm, with the following parameters: n-estimator = 50, max depth = 10, min samples split = 2, and min samples leaf = 1. …”
    Get full text
    Get full text
    Get full text
    Article
  8. 8

    Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…To enhance the selection of most highly ranking features, irrelevant features are ‘pruned’ based on determined boundary threshold. In order to estimate the quality of ‘pruned’ features, self-adaptive DE algorithm is proposed. …”
    Get full text
    Get full text
    Thesis
  9. 9
  10. 10

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

    Published 2023
    “…For future studies, the impact of heterogeneity using a hybrid model with imbalanced data or missing values can be investigated. Ensemble machine learning algorithms such as stacking, XGBoost, and AdaBoost can be used.…”
    Get full text
    Get full text
    Thesis
  11. 11

    Sensorless induction motor speed control for electric vehicles using enhanced hybrid flux estimator with ann-ifoc controller by Sepeeh, Muhamad Syazmie

    Published 2022
    “…Therefore, this project proposed a new mechanism in order to eliminate the speed sensor by adopting an enhanced hybrid flux estimation. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  12. 12
  13. 13

    Classification of heart sound signals for the detection of heart diseases / N. Shamsuddin and M. N. Taib by Shamsuddin, N., Taib, M. N.

    Published 2012
    “…The obtained frequency pattern features were fed to the FFNN and trained using Resilient Backpropagation (RPROP) algorithm. With optimized learning parameter of 0.07, the network gave its best performance at 32-220-6. …”
    Get full text
    Get full text
    Get full text
    Article
  14. 14

    Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Nor Farizan, Zakaria, Mohd Mawardi, Saari

    Published 2023
    “…This paper presents the application of a recent metaheuristic algorithm namely Evolutionary Mating Algorithm (EMA) for optimizing the Deep Learning (DL) parameters to estimate the state of charge (SOC) of a battery for an electric vehicle in the real environment. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  15. 15

    Improved Location And Positioning Utilizing Single MIMO Base Station In IMT-Advanced System by Azmi, Awang Md Isa, Mustafa H., Othman, Zahariah, Manap, Mohd Sa'ari, Mohamad Isa, Mohd Shahril Izuan, Mohd Zin, Mohd Shakir, Md Saat, Zahriladha, Zakaria

    Published 2016
    “…This algorithm based on the angle of arrival (AOA) and angle of departure (AOD) measurement parameter completed the new SMBS algorithm with virtual base station (SMVirBS). …”
    Get full text
    Get full text
    Get full text
    Article
  16. 16

    Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach by Nurnajmin Qasrina Ann, ., Pebrianti, Dwi, Mohamad Fadhil, Abas, Bayuaji, Luhur

    Published 2022
    “…Therefore, it is crucial to assess the parameter of chaotic systems. To solve the issue of parameter estimation for a chaotic system, deep learning is utilized. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  17. 17

    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.…”
    Get full text
    Get full text
    Proceeding Paper
  18. 18
  19. 19

    An improved scatter search algorithm for parameter estimation in large-scale kinetic models of biochemical systems by Remli, Muhammad Akmal, Mohamad, Mohd Saberi, Deris, Safaai, Sinnott, Richard, Napis, Suhaimi

    Published 2019
    “…Methods: This paper proposes an improved scatter search algorithm to address the challenging parameter estimation problem. …”
    Get full text
    Get full text
    Get full text
    Article
  20. 20

    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. …”
    Get full text
    Get full text
    Article