Search Results - (( variable extractions _ algorithm ) OR ( parameter estimation based algorithm ))

Refine Results
  1. 1

    Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

    Published 2025
    “…However, existing RUL prediction approaches have difficulties with variability and nonlinearity that occur during battery degradation, data extraction, feature extraction, hyperparameters optimization, and prediction model uncertainty. …”
    Article
  2. 2
  3. 3

    Development Of Water Quality Index Prediction Model For Penang Rivers Using Artificial Neural Network by Mohd Hamdan, Eleena Yasmeen

    Published 2021
    “…Prior to the development of ANN-based WQI prediction model, the BR algorithm was chosen with two-, three-, four-, five- and six-neuron architectures for 60% and 70% training. …”
    Get full text
    Get full text
    Monograph
  4. 4

    Velocity Field Measurement of a Round Jet using Quantitative Schlieren by Iffa, Emishaw D., Aziz, A. Rashid A., Malik , Aamir Saeed

    Published 2011
    “…The deflection vector estimation was carried out using phase based optical flow algorithms. …”
    Get full text
    Get full text
    Article
  5. 5

    Semiparametric inference procedure for the accelarated failure time model with interval-censored data by Karimi, Mostafa

    Published 2019
    “…A computationally simple two-step iterative algorithm, called estimationapproximation algorithm, is introduced for estimating the parameters of the model on the basis of the rank estimators. …”
    Get full text
    Get full text
    Get full text
    Thesis
  6. 6

    Perturbation stochastic model updating of a bolted structure / Mohamad Azam Shah Aziz Shah by Aziz Shah, Mohamad Azam Shah

    Published 2022
    “…The SMU method based on the improved model was used to predict the variability of the dynamic behaviour of the structure. …”
    Get full text
    Get full text
    Thesis
  7. 7

    Finite impulse response optimizers for solving optimization problems by Ab Rahman, Tasiransurini

    Published 2019
    “…In this work, three new estimation-based metaheuristic algorithms are introduced. …”
    Get full text
    Get full text
    Thesis
  8. 8

    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
  9. 9

    Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems by Kek, Sie Long

    Published 2011
    “…The main idea is the integration of optimal control and parameter estimation. In this work, a simplified model-based optimal control model with adjustable parameters is constructed. …”
    Get full text
    Get full text
    Thesis
  10. 10
  11. 11

    Finite impulse response optimizers for solving optimization problems by Tasiransurini, Ab Rahman

    Published 2019
    “…In this work, three new estimation-based metaheuristic algorithms are introduced. …”
    Get full text
    Get full text
    Thesis
  12. 12
  13. 13

    Simultaneous Computation of Model Order and Parameter Estimation for System Identification Based on Gravitational Search Algorithm by Kamil Zakwan, Mohd Azmi, Pebrianti, Dwi, Zuwairie, Ibrahim, Shahdan, Sudin, Sophan Wahyudi, Nawawi

    Published 2015
    “…In this paper, a technique termed as Simultaneous Model Order and Parameter Estimation (SMOPE), which is specifically based on Gravitational Search Algorithm (GSA) is proposed to combine model order selection and parameter estimation in one process. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  14. 14

    Enhanced segment particle swarm optimization for large-scale kinetic parameter estimation of escherichia coli network model by Mohammed Adam, Kunna Azrag

    Published 2021
    “…However, the large-scale kinetic parameters estimation using optimization algorithms is still not applied to the main metabolic pathway of the E. coli model, and they’re a lack of accuracy result been reported for current parameters estimation using this approach. …”
    Get full text
    Get full text
    Thesis
  15. 15

    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
    “…The most popular method to solve parameter estimation problem is using optimization algorithm that easily trap to local minima and poor in exploitation to find the good solutions. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  16. 16

    Parameter estimation of cocomo model using the jaya algorithm for software cost estimation by Tan, Jie Chee

    Published 2019
    “…This thesis proposed the Jaya algorithm based on estimation of the software based on the COCOMO I model. …”
    Get full text
    Get full text
    Undergraduates Project Papers
  17. 17

    Estimation Of Weibull Parameters Using Simulated Annealing As Applied In Financial Data by Hamza, Abubakar

    Published 2023
    “…The performance of the SA algorithm has been explored in terms of accuracies and estimation errors. …”
    Get full text
    Get full text
    Thesis
  18. 18
  19. 19

    Simultaneous computation of model order and parameter estimation for ARX model based on single swarm and multi swarm simulated Kalman filter by Kamil Zakwan, Mohd Azmi, Zuwairie, Ibrahim, Pebrianti, Dwi, Mohd Saberi, Mohamad

    Published 2017
    “…Simultaneous Model Order and Parameter Estimation (SMOPE) and Simultaneous Model Order and Parameter Estimation based on Multi Swarm (SMOPE-MS) are two techniques of implementing meta-heuristic algorithm to iteratively establish an optimal model order and parameters simultaneously for an unknown system. …”
    Get full text
    Get full text
    Get full text
    Article
  20. 20