Search Results - (( parameter estimation modified algorithm ) OR ( using optimization problems 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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2
Application of conjugate gradient approach for nonlinear optimal control problem with model-reality differences
Published 2018“…Here, the conjugate gradient approach is used to solve the modified model-based optimal control problem, where the optimal solution of the model used is calculated repeatedly, in turn, to update the adjusted parameters on each iteration step. …”
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Application of conjugate gradient approach for nonlinear optimal control problem with model-reality difference
Published 2018“…Here, the conjugate gradient approach is used to solve the modified model-based optimal control problem, where the optimal solution of the model used is calculated repeatedly, in turn, to update the adjusted parameters on each iteration step. …”
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4
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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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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6
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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Modified anfis architecture with less computational complexities for classification problems
Published 2018“…Furthermore, researchers have mainly used metaheuristic algorithms to avoid the problem of local minima in standard learning method. …”
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8
Parameter estimation of multicomponent transient signals using deconvolution and ARMA modelling techniques
Published 2003“…Using an autoregressive moving (ARMA) model whose AR parameters are determined by solving high-order Yule-Walker equations (HOYWE) via the singular value decomposition (SVD) algorithm can alleviate this shortcoming. …”
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Bio-inspired computation: Recent development on the modifications of the cuckoo search algorithm
Published 2017“…Additionally, the influences of various parameter settings regarding cuckoo search are taken into account in order to provide their optimal settings for specific problem classes. …”
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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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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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Improved genetic algorithm for direct current motor high speed controller implemented on field programmable gate array
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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15
Use of AR Block Processing for Estimating the State Variables of Power System
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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Robust techniques for linear regression with multicollinearity and outliers
Published 2016“…The proposed method is formulated by incorporating robust MM-estimator and the modified generalized M-estimator (MGM) in the LRR algorithm. …”
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17
Information Theoretic-based Feature Selection for Machine Learning
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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18
Image watermarking optimization algorithms in transform domains and feature regions
Published 2012“…A series of training patterns are constructed by employing between two images.Moreover,the work takes accomplishing maximum robustness and transparency into consideration.HPSO method is used to estimate the multiple parameters involved in the model. …”
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19
A comprehensive analysis of surface electromyography for control of lower limb exoskeleton
Published 2016“…Obviously, selecting four muscles to attain a full joint moment and motion is not sufficient, therefore we introduced the net joint moment obtained from the inverse dynamics to optimize the predicted joint moment. Initial estimate of the model is obtained from literature review while the Levenderg-Marquardt (LM) method is applied to solve the nonlinear least squares optimization problem. …”
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Parameter estimation of tapioca starch hydrolysis process: application of least squares and genetic algorithm
Published 2005“…The performance of genetic algorithm (GA) in nonlinear kinetic parameter estimation of topiaca starch hydrolysis was studied and compared with Gauss-Newton method. …”
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