Search Results - (( parameter estimation modified algorithm ) OR ( parameter optimization _ algorithm ))
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Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems
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 -
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Modified multi-verse optimizer for nonlinear system identification of a double pendulum overhead crane
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 -
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Optimal parameter estimation of MISO system based on fuzzy numbers / Razidah Ismail ... [et al.]
Published 2006“…The optimal input parameters are determined by the Modified OptimizedDefuzzified Value Theorem. …”
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Simultaneous computation of model order and parameter estimation for ARX model based on single swarm and multi swarm simulated Kalman filter
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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LASSO-type estimations for threshold autoregressive and heteroscedastic time series models.
Published 2020“…In this thesis, we propose Least Absolute Shrinkage and Selection Operator (LASSO) type estimators to perform simultaneous parameter estimation and model selection for five specific univariate and multivariate time series models, and develop several algorithms to compute these estimators. …”
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UMK Etheses -
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Application of conjugate gradient approach for nonlinear optimal control problem with model-reality differences
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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Application of conjugate gradient approach for nonlinear optimal control problem with model-reality difference
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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Identification of continuous-time model of hammerstein system using modified multi-verse optimizer
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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Power System State Estimation In Large-Scale Networks
Published 2010“…The results show that AR methods managed to accurately predict the data and filter the weigthage factors for the bad measurements. Also the WLS algorithm is modified to include Unified Power Flow Controller (UPFC) parameters. …”
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10
Parameter estimation of multicomponent transient signals using deconvolution and ARMA modelling techniques
Published 2003“…In this method of analysis the exponential signal is converted to a convolution model whose input is a train of weighted delta function that contains the signal parameters to be determined.The resolution of the estimated decay rates is poor if the conventional fast Fourier transform (FFT) algorithm is used to analyse the resulting deconvolved data. …”
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Firefly Algorithm based LCL filtered grid-tied STATCOM design for reactive power compensation in SCIG based Micro-grid
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…”
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Development of optimization Alghorithm for uncertain non-linear dynamical system
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 -
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Bio-inspired computation: Recent development on the modifications of the cuckoo search algorithm
Published 2017“…The purpose of this study is to assist potential developers in selecting the most suitable cuckoo search variant, provide proper guidance in future modifications and ease the selection of the optimal cuckoo search parameters. Several researchers have attempted to apply several modifications to the original cuckoo search algorithm in order to advance its effectiveness. …”
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Testing of linear models for optimal control of second-order dynamical system based on model-reality differences
Published 2021“…On this basis, an expanded optimal control problem, which combines system optimization and parameter estimation, is introduced. …”
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Modified anfis architecture with less computational complexities for classification problems
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 -
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Testing of linear models for optimal control of second-order dynamical system based on model-reality differences
Published 2021“…On this basis, an expanded optimal control problem, which combines system optimization and parameter estimation, is introduced. …”
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Testing of linear models for optimal control of second-order dynamical system based on model-reality differences
Published 2021“…On this basis, an expanded optimal control problem, which combines system optimization and parameter estimation, is introduced. …”
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Application of Evolutionary Algorithm for Assisted History Matching
Published 2014“…From the outcome, engineers are able to estimate the future production rate of the well closely based on parameters like pressure, relative permeability and porosity. …”
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