Search Results - (( location detection ((a algorithm) OR (_ algorithm)) ) OR ( swarm optimization model algorithm ))
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1
Evaluation of different peak models of eye blink EEG for signal peak detection using artificial neural network
Published 2016“…Therefore, the purpose of peak detection algorithm is to distinguish an actual peak location from a list of peak candidates. …”
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2
Evaluation Of Different Peak Models Of Eye Blink Eeg For Signal Peak Detection Using Artificial Neural Network
Published 2016“…Therefore, the purpose of peak detection algorithm is to distinguish an actual peak location from a list of peak candidates. …”
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3
Optimized techniques for landslide detection and characteristics using LiDAR data
Published 2018“…Also, six techniques: Ant Colony Optimization (ACO), Gain Ratio (GR), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA), Random forest (RF), and Correlation-based Feature Selection (CFS) were used for the feature selection. …”
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Thesis -
4
An Optimized Semantic Segmentation Framework for Human Skin Detection
Published 2024“…Existing approaches used complex and various heuristic designs of image processing algorithms and deep models customized for skin detection problems. …”
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5
Image watermarking optimization algorithms in transform domains and feature regions
Published 2012“…The achieved tradeoffs from these techniques between imperceptibility and robustness are controversial.To solve this problem,this study proposes the application of artificial intelligent techniques into digital watermarking by using discrete wavelet transform (DWT) and singular value decomposition (SVD).To protect the copyright information of digital images,the original image is decomposed according to two-dimensional discrete wavelet transform.Subsequently the preprocessed watermark with an affined scrambling transform is embedded into the vertical subband (HLm) coefficients in wavelet domain without compromising the quality of the image.The scaling factors are trained with the assistance of Particle Swarm Optimization (PSO).A new algorithmic framework is used to forecast feasibility of hypothesized watermarked images.In addition,the novelty is to associate the Hybrid Particle Swarm Optimization (HPSO),instead of a single optimization,as a model with SVD.To embed and extract the watermark,the singular values of the blocked host image are modified according to the watermark and scaling factors. …”
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6
Development of optimized damage prediction method for health monitoring of ultra high performance fiber-reinforced concrete communication tower
Published 2018“…In addition, a simple procedure is proposed to determine the optimal solution and predict the correlation factor and the frequency of the damaged communication tower by using the particle swarm optimization (PSO) method. …”
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7
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). …”
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8
Malicious URL classification using artificial fish swarm optimization and deep learning
Published 2023“…With this motivation, the current article develops an Artificial Fish Swarm Algorithm (AFSA) with Deep Learning Enabled Malicious URL Detection and Classification (AFSADL-MURLC) model. …”
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Enhanced segment particle swarm optimization for large-scale kinetic parameter estimation of escherichia coli network model
Published 2021“…Thus, this research aimed to estimate large-scale kinetic parameters of the main metabolic pathway of the E. coli model. In this regard, a Local Sensitivity Analysis, Segment Particle Swarm Optimization (Se-PSO) algorithm, and the Enhanced Segment Particle Swarm Optimization (ESe-PSO) algorithm was adapted and proposed to estimate the parameters. …”
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10
Predicting longitudinal dispersion coefficient using ensemble models and optimized multi-layer perceptron models
Published 2024“…The honey badger optimization algorithm (HBOA), salp swarm algorithm (SASA), firefly algorithm (FIFA), and particle swarm optimization algorithm (PASOA) are used to adjust the MULP parameters. …”
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Fitness-guided particle swarm optimization with adaptive Newton-Raphson for photovoltaic model parameter estimation
Published 2025Subjects:Article -
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Improving the Muskingum flood routing method using a hybrid of particle swarm optimization and bat algorithm
Published 2023“…Decision making; Disaster prevention; Floods; Routing algorithms; Water resources; Absolute deviations; Bat algorithms; Comparative analysis; Computational time; Flood routing; Muskingum models; Particle swarm optimization algorithm; Swarm algorithms; Particle swarm optimization (PSO); accuracy assessment; algorithm; comparative study; decision making; flood; flood forecasting; flood routing; numerical method; optimization; parameter estimation; water resource; United Kingdom; United States…”
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Modeling and optimization of multi-holes drilling path using Particle Swarm Optimization
Published 2018“…Later the problem is optimized using Particle Swarm Optimization (PSO) and compared with other algorithms including the new metaheuristics algorithms. …”
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Research Report -
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A hybrid bat�swarm algorithm for optimizing dam and reservoir operation
Published 2023“…Dams; Irrigation; Particle swarm optimization (PSO); Bat algorithms; Global optimal solutions; Hybrid optimization algorithm; Multi-reservoir systems; Optimization algorithms; Optimization modeling; Particle swarm optimization algorithm; Reservoir operation; Reservoirs (water)…”
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Optimization of multi-holes drilling path using particle swarm optimization
Published 2018“…The problem is modeled as traveling salesman problem (TSP) and optimized using Particle Swarm Optimization (PSO). …”
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Book Chapter -
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An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli
Published 2020“…In this study, an Enhanced Segment Particle Swarm Optimization algorithm (ESe-PSO) was proposed for kinetic parameters estimation. …”
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OPTIMIZATION OF PID CONTROLLER PARAMETERS USING ARTIFICIAL FISH SWARM ALGORITHM
Published 2013“…The Literature Review chapter thoroughly describes the Idea of Swarm Intelligence and Swarm Optimization. In methodology, the mathematical model of the algorithm is briefly described. …”
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Final Year Project -
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Capacitated vehicle-routing problem model for scheduled solid waste collection and route optimization using PSO algorithm
Published 2023“…Costs; Efficiency; Routing algorithms; Scheduling; Solid wastes; Vehicle routing; Capacitated vehicle routing problem; Modified particle swarm optimization; Optimized models; Route optimization; Solid waste collection; Threshold waste level; Travel distance; Waste collection; Particle swarm optimization (PSO); fuel; algorithm; numerical model; optimization; routing; solid waste; transport vehicle; waste disposal; algorithm; Article; capacitated vehicle routing problem model; controlled study; cost; decision making; environmental impact; motor vehicle; nonbiological model; particle swarm optimization algorithm; priority journal; problem solving; process optimization; socioeconomics; solid waste management; travel; validation process; economics; solid waste; waste management; Algorithms; Costs and Cost Analysis; Solid Waste; Waste Management…”
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Fractional chaotic ensemble particle swarm optimizer for identifying the single, double, and three diode photovoltaic models� parameters
Published 2023“…Heuristic algorithms; Particle swarm optimization (PSO); Photovoltaic cells; Renewable energy resources; Solar power generation; Commercial applications; Environmental conditions; Fast convergence rate; Meta heuristic algorithm; Optimization algorithms; Parameters estimation; Particle swarm optimizers; PV models; Diodes; algorithm; alternative energy; electrode; model; optimization; parameter estimation; photovoltaic system; temperature effect…”
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Optimal neural network approach for estimating state of energy of lithium-ion battery using heuristic optimization techniques
Published 2023Conference Paper
