Search Results - (( data optimization method algorithm ) OR ( data identification method algorithm ))
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1
Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification
Published 2011“…System identification is a method of determining a mathematical relation between variables and terms of a process based on observed input-output data. …”
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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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3
Using genetic algorithms as image watermarking performance optimizer / Zuhaili Zahid
Published 2008“…Image watermarking is a method to hide a message in an image for transmission of secret data or identification purposes. …”
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4
Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…The data vectors are assigned to the closest cluster and correspondingly to the set, which contains this cluster and an algorithm based on a derivative-free method is applied to the solution of this problem. …”
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5
Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification
Published 2007“…The genetic algorithm approach is widely recognized as an effective and flexible optimization method for system identification. …”
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6
Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification
Published 2007“…he genetic algorithm approach is widely recognized as an effective and flexible optimization method for system identification. …”
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7
System identification using Extended Kalman Filter
Published 2017“…Besides, Extended Kalman Filter (EKF) algorithm was selected in this project as an algorithm for offline estimation data purposes. …”
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Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman Smoother adaptive filter
Published 2015“…The applicability of the proposed methods is tested in three simulated data and one experimental data. …”
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9
Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification
Published 2007“…The genetic algorithm approach is widely recognized as an effective and flexible optimization method for system identification. …”
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10
Tree-based contrast subspace mining method
Published 2020“…The research works involve first preparing the real world numerical and categorical data sets. Then, the tree-based method, the genetic algorithm based parameter values identification of tree-based method, and followed by the genetic algorithm based tree-based method, for numerical data sets are developed and evaluated. …”
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Autoreclosure in Extra High Voltage Lines using Taguchi’s Method and Optimized Neural Networks
Published 2008“…The fault identification prior to reclosing is based on optimized artificial neural network associated with standard Error Back-Propagation, Levenberg Marquardt Algorithm and Resilient Back-Propagation training algorithms together with Taguchi’s Method. …”
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13
Autoreclosure in Extra High Voltage Lines using Taguchi's Method and Optimized Neural Networks
Published 2009“…The fault identification prior to reclosing is based on optimized artificial neural network associated with standard Error Back-Propagation, Levenberg Marquardt Algorithm and Resilient Back-Propagation training algorithms together with Taguchi’s Method. …”
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14
Implementation of Evolutionary Algorithms to Parametric Identification of Gradient Flexible Plate Structure
Published 2023“…A square aluminium plate experimental rig with a gradient of 30° and all edges clamped were designed and fabricated to acquire input-output vibration data experimentally. This input-output data was then applied in a system identification method, which used an evolutionary algorithm with a linear autoregressive with exogenous (ARX) model structure to generate a dynamic model of the system. …”
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15
Implementation of Evolutionary Algorithms to Parametric Identification of Gradient Flexible Plate Structure
Published 2023“…A square aluminium plate experimental rig with a gradient of 30° and all edges clamped were designed and fabricated to acquire input-output vibration data experimentally. This input-output data was then applied in a system identification method, which used an evolutionary algorithm with a linear autoregressive with exogenous (ARX) model structure to generate a dynamic model of the system. …”
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Taguchi's method for optimized neural network based autoreclosure in extra high voltage lines
Published 2008“…The fault identification prior to reclosing is based on optimized artificial neural network associated with Levenberg Marquardt algorithm to train the ANN and Taguchi's Method to find optimal parameters of the algorithm and number of hidden neurons. …”
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17
Hybridized firefly algorithm for multi-objective radio frequency identification (RFID) network planning
Published 2017“…The technique was combining the Density Based Clustering method (DBSCAN) and firefly algorithm. Empirical tests were conducted on six standard RFID benchmark sets with random and clustered topologies. …”
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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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19
Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman smoother adaptive filter
Published 2015“…The applicability of the proposed methods is tested in three simulated data and one experimental data. …”
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20
Hybridization of nonlinear sine cosine and safe experimentation dynamics algorithms for solving control engineering optimization problems
Published 2024“…The empirical assessment of these proposed methods encompasses a diverse set of 23 benchmark functions, demonstrating their efficacy comparable to well-established metaheuristic algorithms such as as the Grey Wolf Optimizer (GWO), Multi-Verse Optimization (MVO), Sine Cosine Algorithm (SCA), Ant Lion Optimizer (ALO), Moth-Flame Optimization Algorithm (MFO), and Grasshopper Optimization Algorithm (GOA). …”
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