Search Results - (( motion evaluation swarm algorithm ) OR ( shape identification mining algorithm ))*
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A review on particle swarm optimization algorithm and its variants to human motion tracking
Published 2014“…Several approaches have been proposed in the literature using different techniques.However, conventional approaches such as stochastic particle filtering have shortcomings in computational cost, slowness of convergence, suffers from the curse of dimensionality and demand a high number of evaluations to achieve accurate results. Particle swarm optimization (PSO) is a population-based globalized search algorithm which has been successfully applied to address human motion tracking problem and produced better results in high-dimensional search space.This paper presents a systematic literature survey on the PSO algorithm and its variants to human motion tracking. …”
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Discovering association rules for mining images datasets: a proposal
Published 2005“…The algorithm has four major steps: feature extraction, object identification, auxiliary image creation and object mining. …”
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Particle swarm optimization with deep learning for human action recognition
Published 2021“…This decreases the detection efficiency and degrades the target tracking output. Also, the current motion target detection algorithms extract features from the relevant object only if the moving object has complex texture features. …”
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Multi-state PSO GSA for solving discrete combinatorial optimization problems
Published 2016“…Two examples of meta-heuristics are Particle swarm optimization (PSO) and gravitational search algorithm (GSA), which are based on the social behavior of bird flocks and the Newton's law of gravity and the law of motion, respectively. …”
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Synchronous gravitational search algorithm vs asynchronous gravitational search algorithm: a statistical analysis
Published 2014“…Gravitational search algorithm (GSA) is a new member of swarm intelligence algorithms. …”
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Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan
Published 2020“…In the modeling phase, amongst all DM algorithms, the applicability of machine learning, artificial intelligence and statistical data mining techniques were examined using Support Vector Machine (SVM), Artificial Neural Network (ANN) and Classification and Regression Tree (CART) to detect the hidden patterns in vibration data. …”
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EMG Feature Selection And Classification Using A Pbest-Guide Binary Particle Swarm Optimization
Published 2019“…After which pbest-guide binary particle swarm optimization (PBPSO) is used to evaluate the most informative features from the original feature set. …”
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Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem
Published 2015“…Gravitational search algorithm swarm (GSA) is a metaheuristic optimization algorithm, which is based on the Newton's law of gravity and the law of motion, has been successfully applied to solve various optimization problems in real-value search space. …”
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3D virtual modelling and stabilization control of triple links inverted pendulum on two-wheeled system using enhanced interval type-2 fuzzy logic control
Published 2020“…Two optimization algorithms are presented in this work which are Spiral Dynamic Algorithm (SDA) and Particle Swarm Optimization (PSO). …”
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Liquid Slosh Control By Implementing Model-Free PID Controller With Derivative Filter Based On PSO
Published 2020“…The PSO tuning method is compared by heuristic tuning method in order to show the effectiveness of the proposed tuning approach. The performance evaluations of the proposed tuning method are based on the ability of the tank to follow the input in horizontal motion and liquid slosh level reduction in time domain. …”
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Liquid slosh control by implementing model-free PID controller with derivative filter based on PSO
Published 2020“…The PSO tuning method is compared by heuristic tuning method in order to show the effectiveness of the proposed tuning approach. The performance evaluations of the proposed tuning method are based on the ability of the tank to follow the input in horizontal motion and liquid slosh level reduction in time domain. …”
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Hardware-in-the-loop study of a hybrid active force control scheme of an upper-limb exoskeleton for passive stroke rehabilitation
Published 2018“…A hardware-in-the-loop simulation is carried out to evaluate the appropriate gains of both the PD and the AFC inertial parameter gained that is tuned via the SKF algorithm. …”
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Hardware-in-the-loop study of a hybrid active force control scheme of an upper-limb exoskeleton for passive stroke rehabilitation
Published 2018“…A hardware-in-the-loop simulation is carried out to evaluate the appropriate gains of both the PD and the AFC inertial parameter gained that is tuned via the SKF algorithm. …”
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Optimization of slosh suppression system through data-driven state feedback controller
Published 2024“…The nature of the slosh motion phenomenon has commonly been found in various engineering applications. …”
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An enhancement particle-based method for dynamic object tracking
Published 2016“…Thus, to address the accuracy of object detection, we proposed a new method of dynamic template matching using Global best Local Neighborhood in Particle Swarm Optimization (GbLN-PSO). In this study, feature-based approach using a GbLN-PSO algorithm will be applied to search the minimum value of dynamic template matching process. …”
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Development of optimized damage prediction method for health monitoring of ultra high performance fiber-reinforced concrete communication tower
Published 2018“…Therefore, this study aims to develop a new health monitoring system for communication towers based on AdaBoost, Bagging, and RUSBoost algorithms as hybrid algorithm, which can predict the damage by using noisy, random, unstable, and skewed frequency data with high accuracy. …”
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PID-PSO DC motor position controller design for ankle rehabilitation system
Published 2023“…The transfer function is a model in Matlab software to validate the performance of the control system through simulation compared with real-time experiments. Next, the control algorithms are proposed to design and implement the Proportional-Integral-Derivative (PID) with Particle Swarm Optimization (PSO) controller technique for optimal Proportional (Kp), Integral (Ki) and Derivative (Kd) gains. …”
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