Search Results - (( data application system algorithm ) OR ( parameters estimation method algorithm ))
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1
Estimation in spot welding parameters using genetic algorithm
Published 2007“…Genetic algorithm (GA) used as parameter estimation method for a model structure. …”
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2
Orthogonal least square algorithm and its application for modelling suspension system
Published 2001“…Modelling based on input and output data is known as system identification. One of the issues in system identification is the parameter estimation and model structure selection where various methods have been studied including the orthogonal least square algorithm. …”
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3
Estimation of photovoltaic models using an enhanced Henry gas solubility optimization algorithm with first-order adaptive damping Berndt-Hall-Hall-Hausman method
Published 2024“…It ensures that the obtained parameters reflect the true characteristics of the PV system, leading to more accurate and reliable results in various applications. …”
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Simultaneous Computation of Model Order and Parameter Estimation for System Identification Based on Gravitational Search Algorithm
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. …”
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5
Mixed Unscented Kalman Filter and differential evolution for parameter identification
Published 2013“…UKF have known to be a typical estimation technique used to estimate the state vectors and parameters of nonlinear dynamical systems and DE is one of the most powerful stochastic real-parameter optimization algorithms. …”
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6
Power System State Estimation In Large-Scale Networks
Published 2010“…Also the WLS algorithm is modified to include Unified Power Flow Controller (UPFC) parameters. …”
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7
A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. Then, the developed algorithm is implemented to estimate the parameters of the Lorenz system. …”
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8
Simultaneous Computation of Model Order and Parameter Estimation of a Heating System Based on Gravitational Search Algorithm for Autoregressive with Exogenous Inputs
Published 2015“…The next stage is to estimate the parameters of the model and finally, the mathematical model is validated. …”
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9
Parameter estimation of essential amino acids in Arabidopsis thaliana using hybrid of bees algorithm and harmony search
Published 2019“…In model building, the task of parameter estimation is difficult due to the huge numbers of kinetics parameters involved. …”
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10
Analysis of Toothbrush Rig Parameter Estimation Using Different Model Orders in Real Coded Genetic Algorithm (RCGA)
Published 2024“…The influence of conventional genetic algorithm parameter - generation gap has been investigated too. …”
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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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12
A hybrid metaheuristic algorithm for identification of continuous-time Hammerstein systems
Published 2021“…The proposed hybrid method also achieved better performance in modeling of the twin-rotor system as well as the flexible manipulator system and provided better solutions compared to other optimization methods including Particle Swarm Optimizer, Grey Wolf Optimizer, Multi-Verse Optimizer and Sine Cosine Algorithm.…”
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13
Identification of continuous-time hammerstein system using sine cosine algorithm
Published 2019“…The SCA based method is then used to estimate the parameters in both the linear and nonlinear parts based on the given input and output data. …”
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14
Reduced rank technique for joint channel estimation and joint data detection in TD-SCDMA systems
Published 2013“…This paper presents a novel channel estimation method with low complexity, which relies on reducing the rank order of the total channel matrix H. …”
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15
Reduced-rank technique for joint channel estimation in TD-SCDMA systems.
Published 2013“…This paper presents a novel channel estimation method with low complexity, which relies on reducing the rank order of the total channel matrix H. …”
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16
Evaluating power efficient algorithms for efficiency and carbon emissions in cloud data centers: a review
Published 2015“…CloudSim simulator is used to implement the algorithms on an IaaS cloud infrastructure, to calculate the power consumption, and to analyze each algorithm's behavior for different parameters. …”
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17
Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms
Published 2020“…Firstly, an improved EM (IEM) algorithm is presented to estimate the five parameters of the single PV-module system. …”
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18
Field data-based mathematical modeling by Bode equations and vector fitting algorithm for renewable energy applications
Published 2018“…The most powerful features of this method is the ability to model irregular or randomly shaped data and to be applied to any algorithms that estimating models using frequency-domain data to provide state-space or transfer function for the model.…”
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Scene illumination classification based on histogram quartering of CIE-Y component
Published 2014“…Those algorithms which performed estimation carrying out lots of calculation that leads in expensive methods in terms of computing resources. …”
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20
Identification of continuous-time model of hammerstein system using modified multi-verse optimizer
Published 2021“…Multi-Verse Optimizer (MVO) is one of the most recent robust nature-inspired metaheuristic algorithm. It has been successfully implemented and used in various areas such as machine learning applications, engineering applications, network applications, parameter control, and other similar applications to solve optimization problems. …”
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