Search Results - (( model estimation based algorithm ) OR ( parameters estimation swarm algorithm ))

Refine Results
  1. 1

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

    Published 2021
    “…In this regard, a Local Sensitivity Analysis, Segment Particle Swarm Optimization (Se-PSO) algorithm, and the Enhanced Segment Particle Swarm Optimization (ESe-PSO) algorithm was adapted and proposed to estimate the parameters. …”
    Get full text
    Get full text
    Thesis
  2. 2
  3. 3

    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
  4. 4
  5. 5

    Simultaneous Computation of Model Order and Parameter Estimation for Arx Model Based on Multiswarm Particle Swarm Optimization by Kamil Zakwan, Mohd Azmi, Zuwairie, Ibrahim

    Published 2015
    “…Simultaneous Model Order and Parameter Estimation (SMOPE) is a method of utilizing meta-heuristic algorithm to iteratively determine an optimal model order and parameters simultaneously for an unknown system. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  6. 6

    PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah by Abdullah, Siti Muniroh

    Published 2017
    “…The parameter estimation step is concerned with the estimation of model parameters once the structure is known. …”
    Get full text
    Get full text
    Thesis
  7. 7

    Accuracy enhancement for zone mapping of a solar radiation forecasting based multi-objective model for better management of the generation of renewable energy by Ehteram M., Ahmed A.N., Fai C.M., Afan H.A., El-Shafie A.

    Published 2023
    “…Air quality; Decision making; Forecasting; Fuzzy inference; Fuzzy neural networks; Fuzzy systems; Genetic algorithms; Inference engines; Mapping; Mean square error; Multiobjective optimization; Optimal systems; Particle swarm optimization (PSO); Quality control; Renewable energy resources; Solar radiation; Uncertainty analysis; Adaptive neuro-fuzzy inference system; ANFIS; Multi objective algorithm; Multi objective particle swarm optimization; Multi-objective genetic algorithm; Renewable energies; Renewable energy generation; Solar radiation forecasting; Parameter estimation…”
    Article
  8. 8

    Fractional chaotic ensemble particle swarm optimizer for identifying the single, double, and three diode photovoltaic models� parameters by Yousri D., Thanikanti S.B., Allam D., Ramachandaramurthy V.K., Eteiba M.B.

    Published 2023
    “…Heuristic algorithms; Particle swarm optimization (PSO); Photovoltaic cells; Renewable energy resources; Solar power generation; Commercial applications; Environmental conditions; Fast convergence rate; Meta heuristic algorithm; Optimization algorithms; Parameters estimation; Particle swarm optimizers; PV models; Diodes; algorithm; alternative energy; electrode; model; optimization; parameter estimation; photovoltaic system; temperature effect…”
    Article
  9. 9
  10. 10

    Joint torque estimation model of surface electromyography(sEMG) based on swarm intelligence algorithm for robotic assistive device by Nurhanim, K., Elamvazuthi, I., Vasant, P., Ganesan, T., Parasuraman, S., Ahamed Khan, M.K.A.

    Published 2014
    “…This paper discusses the mapping of surface electromyography signals (sEMG) to torque for robotic rehabilitation. Particle swarm optimization (PSO) has been applied as a control algorithm for a number of selected mathematical models. sEMG signals were determined as input data to the mathematical model where parameters of the mathematical model were optimized using PSO. …”
    Get full text
    Get full text
    Conference or Workshop Item
  11. 11
  12. 12

    Optimal parameter estimation of permanent magnet synchronous motor by using Mothflame optimization algorithm / Abdolmajid Dejamkhooy and Sajjad Asefi by Dejamkhooy, Abdolmajid, Asefi, Sajjad

    Published 2018
    “…Simulation results and their comparison with Particle Swarm Optimization based method show high performance and good ability of the proposed method in PMSM parameter estimation.…”
    Get full text
    Get full text
    Get full text
    Article
  13. 13

    Improving the Muskingum flood routing method using a hybrid of particle swarm optimization and bat algorithm by Ehteram M., Othman F.B., Yaseen Z.M., Afan H.A., Allawi M.F., Malek M.B.A., Ahmed A.N., Shahid S., Singh V.P., El-Shafie A.

    Published 2023
    “…Decision making; Disaster prevention; Floods; Routing algorithms; Water resources; Absolute deviations; Bat algorithms; Comparative analysis; Computational time; Flood routing; Muskingum models; Particle swarm optimization algorithm; Swarm algorithms; Particle swarm optimization (PSO); accuracy assessment; algorithm; comparative study; decision making; flood; flood forecasting; flood routing; numerical method; optimization; parameter estimation; water resource; United Kingdom; United States…”
    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

    Firefly Algorithm based LCL filtered grid-tied STATCOM design for reactive power compensation in SCIG based Micro-grid by Saxena N.K., Gupta A.R., Mekhilef S., Gao W.D., Kumar A., Gupta V., Netto R.S., Kanungo A.

    Published 2023
    “…Bioluminescence; Biomimetics; Electric current regulators; Electric power system control; Electric power transmission networks; Electric power utilization; Parameter estimation; Particle swarm optimization (PSO); Power control; Quality control; Reactive power; Static synchronous compensators; Transient analysis; Filter designs; Firefly algorithms; LCL filters; Microgrid; Particle swarm; Particle swarm optimization; Reactive power compensation; Real and reactive power; SCIG; Swarm optimization; Genetic algorithms…”
    Article
  16. 16

    Simultaneous computation of model order and parameter estimation for system identification based on opposition-based simulated Kalman filter by Badaruddin, Muhammad, Kamil Zakwan, Mohd Azmi, Zuwairie, Ibrahim, Ahmad Afif, Mohd Faudzi, Pebrianti, Dwi

    Published 2018
    “…Simultaneous Model Order and Parameter Estimation (SMOPE) has been proposed to address system identification problem efficiently using optimization algorithms. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  17. 17

    Battery remaining useful life estimation based on particle swarm optimization-neural network by Zuriani, Mustaffa, Mohd Herwan, Sulaiman

    Published 2024
    “…Concerning that matter, this study proposed hybrid Particle Swarm Optimization–Neural Network (PSO NN) for estimating battery RUL. …”
    Get full text
    Get full text
    Get full text
    Article
  18. 18

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

    Published 2015
    “…Three steps of improvements had been made to increase the modeling capacity of input-output models. 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.…”
    Get full text
    Get full text
    Thesis
  19. 19

    Nonlinear auto-regressive model structure selection using binary particle swarm optimization algorithm / Ahmad Ihsan Mohd Yassin by Mohd Yassin, Ahmad Ihsan

    Published 2014
    “…System Identification (SI) is a control engineering discipline concerned with the discovery of mathematical models based on dynamic measurements collected from the system. …”
    Get full text
    Get full text
    Book Section
  20. 20