Search Results - (( data segmentation using algorithm ) OR ( simulation optimization _ algorithm ))
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Estimation of small-scale kinetic parameters of escherichia coli (E. coli) model by enhanced segment particle swarm optimization algorithm ese-pso
Published 2023“…The numerical findings indicate a good agreement between the observed and predicted data. In this regard, the result of the ESe-PSO algorithm achieved superior accuracy compared with the Segment Particle Swarm Optimization (Se-PSO), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Differential Evolution (DE) algorithms. …”
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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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A generalized laser simulator algorithm for optimal path planning in constraints environment
Published 2022“…The results demonstrated that the proposed method could generate an optimal collision-free path. Moreover, the proposed algorithm result are compared to some common algorithms such as the A* algorithm, Probabilistic Road Map, RRT, Bi-directional RRT, and Laser Simulator algorithm to demonstrate its effectiveness. …”
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Segment Particle Swarm Optimization Adoption for Large-Scale Kinetic Parameter Identification of Metabolic Network Model
Published 2018“…However, this paper focuses on adopting segment particle swarm optimization (PSO) and PSO algorithms for large-scale kinetic parameters identification. …”
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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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6
A Novel Hybrid Deep Learning Model Based on Simulated Annealing and Cuckoo Search Algorithms for Automatic Radiomics-Based COVID-19 Diagnosis
Published 2025“…To further enhance COVID-19 lesion estimation, novel optimization strategies, including a hybrid simulated annealing-cuckoo search (SA-CS) algorithm, are introduced alongside the original SA method. …”
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Segment particle swarm optimization adoption for large-scale kinetic parameter identification of escherichia coli metabolic network model
Published 2018“…However, this paper focuses on adopting segment particle swarm optimization (PSO) and PSO algorithms for large-scale kinetic parameters identification. …”
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Mobile data gathering algorithms for wireless sensor networks
Published 2014“…ZDG-MME algorithm is able to segment the deployment field into two divisions and forward the tailored data to the BS. …”
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9
Novel algorithm for mobile robot path planning in constrained environment
Published 2021“…The results demonstrated that the proposed method is able to generate efficiently an optimal collision-free path. Moreover, the performance of the proposed method was compared with the A-star and laser simulator (LS) algorithms in terms of path length, computational time and path smoothness. …”
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10
Novel algorithm for mobile robot path planning in constrained environment
Published 2022“…The results demonstrated that the proposed method is able to generate efficiently an optimal collision-free path. Moreover, the performance of the proposed method was compared with the A-star and laser simulator (LS) algorithms in terms of path length, computational time and path smoothness. …”
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11
Novel algorithm for mobile robot path planning in constrained environment
Published 2022“…The results demonstrated that the proposed method is able to generate efficiently an optimal collision-free path. Moreover, the performance of the proposed method was compared with the A-star and laser simulator (LS) algorithms in terms of path length, computational time and path smoothness. …”
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Deep learning-based item classification for retail automation
Published 2025“…Real-time processing was achieved through the integration of object detection algorithms like YOLO and image segmentation techniques. …”
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Reliable low power network protocol in IoT for agriculture field
Published 2024“…An Internet of Things (IoT) sensor network consists of sensor nodes which sample and send data to the base station. Agriculture is one sector which makes use of IoT sensor networks for collecting data on the growing environment of crops for farmers to perform adjustments for optimal crop growth. …”
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Modeling Of Electrical Distribution Networks With Particle Swarm Optimization Technique For The Improvement Of Voltage Profile And Loss Reduction
Published 2016“…The data of series impedance is also used to investigate power flow in all segments in the distribution system. …”
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15
Customer segmentation on clustering algorithms
Published 2023“…This report presents an analysis of customer segmentation using various clustering algorithms, including k-means, DBSCAN, GMM, and RFM. …”
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16
Application Of Multi-Layer Perceptron Technique To Detect And Locate The Base Of A Young Corn Plant
Published 2007“…Multi-layer perceptron (MLP) neural network trained using backpropagation algorithm is used to segment the color image. …”
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Segmentation of MRI brain images using statistical approaches
Published 2011“…The Gaussian Mixture Model (GMM) is a clustering algorithm that is commonly used for brain MRI segmentation. …”
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19
Sizes of Superpixels and their Effect on Interactive Segmentation
Published 2021“…Despite the fact that it is used as a pre-processing step in many interactive segmentation algorithms, less studies had been conducted to assess the effects of the size of superpixels required by interactive segmentation algorithms to achieve an optimal result. …”
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Proceeding -
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A new hybrid technique for nosologic segmentation of primary brain tumors / Shafaf Ibrahim
Published 2015“…On the other hand, the ANFIS is found to have limited pixel detection in nosologic segmentation of primary brain tumors. The CAPSOCA was proven to be the best algorithm for nosologic segmentation of primary brain tumors from the MRI images data. …”
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