Search Results - (( parameter optimization modified algorithm ) OR ( parameter estimation system algorithm ))

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  1. 1

    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. …”
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    Thesis
  2. 2

    Modified multi-verse optimizer for nonlinear system identification of a double pendulum overhead crane by Julakha, Jahan Jui, Mohd Ashraf, Ahmad, Muhammad Ikram, Mohd Rashid

    Published 2021
    “…The efficiency of the proposed HMVOSCA algorithm is evaluated using the convergence curve, parameter estimation error, bode plot, function plot, and Wilcoxon's test method. …”
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    Conference or Workshop Item
  3. 3

    Optimal parameter estimation of MISO system based on fuzzy numbers / Razidah Ismail ... [et al.] by Ismail, Razidah, Ahmad, Tahir, Ahmad, Shamsuddin, Ahmad, Rashdi Shah

    Published 2006
    “…Thus, this paper discusses the development of a Fuzzy State Space algorithm for optimal parameter estimation in multiple-input single-output (MISO) system based on fuzzy numbers. …”
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    Article
  4. 4

    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. …”
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    Article
  5. 5

    Identification of continuous-time model of hammerstein system using modified multi-verse optimizer by Most. Julakha, Jahan Jui

    Published 2021
    “…his thesis implements a novel nature-inspired metaheuristic optimization algorithm, namely the modified Multi-Verse Optimizer (mMVO) algorithm, to identify the continuous-time model of Hammerstein system. …”
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    Thesis
  6. 6

    Application of conjugate gradient approach for nonlinear optimal control problem with model-reality differences by Leong, Wah June, Sie, Long Kek, Teo, Kok Lay, Sim, Sy Yi

    Published 2018
    “…In doing so, an expanded optimal control problem is introduced such that system optimization and parameter estimation are mutually interactive. …”
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    Article
  7. 7

    Application of conjugate gradient approach for nonlinear optimal control problem with model-reality difference by Sie, Long Kek, Wah, June Leong, Sy, Yi Sim, Kok, Lay Teo

    Published 2018
    “…In doing so, an expanded optimal control problem is introduced such that system optimization and parameter estimation are mutually interactive. …”
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    Article
  8. 8

    Power System State Estimation In Large-Scale Networks by NURSYARIZAL MOHD NOR, NURSYARIZAL

    Published 2010
    “…The developed program is suitable either to estimate the UPFC controller parameters or to estimate these parameter values in order to achieve the given control specifications in addition to the power system state variables.…”
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    Thesis
  9. 9

    Parameter estimation of multicomponent transient signals using deconvolution and ARMA modelling techniques by Salami, Momoh Jimoh Emiyoka, Sidek, Shahrul Na'im

    Published 2003
    “…The effect of sampling conditions, noise level, number of components and relative sizes of the signal parameters on the performance of this modified method of analysis is examined in this paper. …”
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    Article
  10. 10

    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
  11. 11

    Development of optimization Alghorithm for uncertain non-linear dynamical system by Abdul Aziz, Mohd. Ismail, Yaacob, Nazeeruddin, Mohd. Said, Norfarizan, Hamzah, Nor Hazadura

    Published 2004
    “…An algorithm that definitely can satisfy the objectives is the Dynamic Integrated Systems Optimization and Parameter Estimation (DISOPE) algorithm. …”
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    Monograph
  12. 12

    Testing of linear models for optimal control of second-order dynamical system based on model-reality differences by Kek, Sie Long, Sim, Sy Yi, Chen, Chuei Yee

    Published 2021
    “…On this basis, an expanded optimal control problem, which combines system optimization and parameter estimation, is introduced. …”
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    Article
  13. 13

    Testing of linear models for optimal control of second-order dynamical system based on model-reality differences by Kek, Sie Long, Sim, Sy Yi, Yee Chen, Yee Chen

    Published 2021
    “…On this basis, an expanded optimal control problem, which combines system optimization and parameter estimation, is introduced. …”
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    Article
  14. 14

    Testing of linear models for optimal control of second-order dynamical system based on model-reality differences by Kek, Sie Long, Sy, Sy Yi, Chuei, Yee Chen

    Published 2021
    “…On this basis, an expanded optimal control problem, which combines system optimization and parameter estimation, is introduced. …”
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    Article
  15. 15

    Modified anfis architecture with less computational complexities for classification problems by Talpur, Noureen

    Published 2018
    “…The results show that the proposed modified ANFIS architecture with gaussian membership function and Artificial Bee Colony (ABC) optimization algorithm, on average has achieved classification accuracy of 99.5% with 83% less computational complexity.…”
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    Thesis
  16. 16

    Improved genetic algorithm for direct current motor high speed controller implemented on field programmable gate array by Alkhafaji, Falih Salih

    Published 2019
    “…There are many researches have been done to optimize PI controller based evolutionary algorithm, such as Genetic Algorithm (GA). …”
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    Thesis
  17. 17

    Use of AR Block Processing for Estimating the State Variables of Power System by Mohd Nor, Nursyarizal, Jegatheesan, Ramiah, Perumal, Nallagownden

    Published 2008
    “…Samples of the local utility network for 103-bus parameter are collected and simulated using Burg and Modified Covariance algorithm to estimate the state variables. …”
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    Conference or Workshop Item
  18. 18

    Modeling of cupping suction system based on system identification method by Kavindran, Suresh

    Published 2022
    “…By minimizing integral square errors, fractional order model parameters were optimized (ISE). The results reveal that the better the precision of the modelling cupping system parameter, the lower the error. …”
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    Undergraduates Project Papers
  19. 19

    Ant colony optimization (ACO) technique for reactive power planning in power system stability assessment / Mohd Rozely Kalil by Kalil, Mohd Rozely

    Published 2008
    “…The ORPD is implemented to the system by injecting reactive power to the generator buses, while OTTCS aimed to modify the transmission line parameters in order to improve voltage profile and also to reduce total loss in the system. …”
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    Thesis
  20. 20

    Information Theoretic-based Feature Selection for Machine Learning by Muhammad Aliyu, Sulaiman

    Published 2018
    “…Three major factors that determine the performance of a machine learning are the choice of a representative set of features, choosing a suitable machine learning algorithm and the right selection of the training parameters for a specified machine learning algorithm. …”
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    Thesis