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An adept edge detection algorithm for human knee osteoarthritis images
Published 2023“…In this paper, Sobel edge detection operator and its enhanced algorithm are first discussed in terms of optimal thresholding in C language under Linux platform. …”
Conference Paper -
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Artificial neural networks and genetic algorithm for transformer winding/insulation faults
Published 2008“…Genetic Algorithm is used to derive the optimal key gas ratios to enhance the accuracy of fault detection. …”
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3
Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm
Published 2023“…It provides an increased convergence and globally optimized solutions. The algorithm has been tested using actual customer consumption data from SESB. 10 fold cross validation method is used to confirm the consistency of the detection accuracy. …”
Conference Paper -
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Advanced chirped spectral modulation technique and particle swarm optimization algorithms for effective indoor air pollution detection and monitoring
Published 2025“…To address this challenge, optimization algorithms such as the Particle Swarm Optimization (PSO) algorithm have shown promise. …”
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Optimizing the performance of mobile malware detection using the indexing rule
Published 2024journal::journal article -
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Hybrid Artificial Bee Colony Algorithm for t-Way Interaction Test Suite Generation
Published 2019“…This is called hybrid artificial bee colony (HABC) strategy, which is based on hybridize of an artificial bee colony (ABC) algorithm with a particle swarm optimization (PSO) algorithm. …”
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SINR improvement using Firefly Algorithm (FA) for Linear Constrained Minimum Variance (LCMV) beamforming technique
Published 2023Conference Paper -
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Particle swarm optimization with deep learning for human action recognition
Published 2021“…The features are reduced using the particle swarm optimization detection technique in video image sequences to reduce the computational complexity. …”
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Cluster merging based on weighted Mahalanobis distance with application in digital mammography
Published 1998“…Properties of the new algorithm are presented by examining the clustering quality for codebooks designed with the proposed method and another common method that uses Euclidean distance. …”
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10
A hybrid deep learning-based unsupervised anomaly detection in high dimensional data
Published 2022“…The first is the dataset class imbalance, which solved using SMOTE technique. The second issue is the poor performance, which can be solved using one of the optimization algorithms. …”
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Identifying diseases and diagnosis using machine learning
Published 2023“…The method that is use to optimize the criterion efficiency that depend on the previous experience is known as machine learning. …”
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Compressing and improving fuzzy rules using genetic algorithm and its application to fault detection
Published 2023Conference Paper -
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Nature-Inspired Drone Swarming for Wildfires Suppression Considering Distributed Fire Spots and Energy Consumption
Published 2024“…Our quantitative tests show that the improved model has the best coverage (95.3%, 84.3% and 65.8%, respectively) compared to two other methods Levy Flight (LF) algorithm and Particle Swarm Optimization (PSO), which use the same initial parameter values. …”
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Extraction and reconstruction of retinal vasculature
Published 2007“…The reconstruction technique reduces the required number of seeds to near optimal for the region growing process. It also overcomes poor performance of current seed-based methods, especially with low and inconsistent contrast images as normally seen in vasculature regions of fundus images. …”
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Survey on Clustered Routing Protocols Adaptivity for Fire Incidents: Architecture Challenges, Data Losing, and Recommended Solutions
Published 2025“…Thus, developing an effective routing algorithm to optimize network functionality is a big concern. …”
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A multi-nets ANN model for real-time performance-based automatic fault diagnosis of industrial gas turbine engines
Published 2017“…Two back-propagation training algorithms, namely the Levenberg–Marquardt and Bayesian regularization algorithms, and the k-fold cross-validation technique, were employed to train the optimal networks using a training data set. …”
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