Search Results - (( location detection model algorithm ) OR ( based optimization means algorithm ))*
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Segmentation of pulmonary cavity in lung CT scan for tuberculosis disease
Published 2024“…The algorithm, first, calculates the optimal threshold for separating the lesion from the background region. …”
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Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines
Published 2020“…The earlier intelligent approach presented an offline approach using only faulty line parameters for intelligent classifier model training to detect, classify and locate faults. …”
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Enhanced recognition methods for text and slider CAPTCHA vulnerability assessment
Published 2025“…By comparing them with the benchmark models in terms of recognition accuracy, precision, computational complexity, storage space, and other metrics, the superiority of our proposed algorithm is proved. …”
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Robust estimation methods for fixed effect panel data model having block-concentrated outliers
Published 2019“…Not much research has been done on method of detecting HLPs for panel data. Hence, we have proposed Robust Diagnostic-F (RDF) to remedy the problem of masking and swamping in detecting HLPs. …”
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5
Modified damage location indices in beam-like structure: Analytical study
Published 2011“…The modified algorithms are able to detect the damage wherever its location, applying even to cases of multi damage locations. …”
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Optimal neural network approach for estimating state of energy of lithium-ion battery using heuristic optimization techniques
Published 2023Conference Paper -
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Optimized clustering with modified K-means algorithm
Published 2021“…Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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Detection of leak size and its location in a water distribution system by using K-NN / Nasereddin Ibrahim Sherksi
Published 2020“…This thesis proposes a classification model to detect water leakage, focusing on finding water leakage’s location and size, using K-Nearest Neighbour (K-NN) classification method. …”
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10
Impact of evolutionary algorithm on optimization of nonconventional machining process parameters
Published 2025“…This paper presents the optimization of laser beam machining in additive manufacturing of polymer-based material parameters, specifically focusing on cutting speed, gas pressure of nitrogen, and focal point locations, to achieve optimal mean surface roughness. …”
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Document clustering based on firefly algorithm
Published 2015“…Document clustering is widely used in Information Retrieval however, existing clustering techniques suffer from local optima problem in determining the k number of clusters.Various efforts have been put to address such drawback and this includes the utilization of swarm-based algorithms such as particle swarm optimization and Ant Colony Optimization.This study explores the adaptation of another swarm algorithm which is the Firefly Algorithm (FA) in text clustering.We present two variants of FA; Weight- based Firefly Algorithm (WFA) and Weight-based Firefly Algorithm II (WFAII).The difference between the two algorithms is that the WFAII, includes a more restricted condition in determining members of a cluster.The proposed FA methods are later evaluated using the 20Newsgroups dataset.Experimental results on the quality of clustering between the two FA variants are presented and are later compared against the one produced by particle swarm optimization, K-means and the hybrid of FA and -K-means. …”
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Fuzzy C-Mean And Genetic Algorithms Based Scheduling For Independent Jobs In Computational Grid
Published 2006“…Our model presents the method of the jobs classifications based mainly on Fuzzy C-Mean algorithm and mapping the jobs to the appropriate resources based mainly on Genetic algorithm. …”
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Modified archive update mechanism of multi-objective particle swarm optimization in fuzzy classification and clustering
Published 2022“…Among multi-objective evolutionary algorithms proposed in the literature, particle swarm optimization (PSO)-based multi-objective (MOPSO) algorithm has been cited to be the most representative. …”
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Fraud detection in shipping industry based on location using machine learning comparison techniques
Published 2023“…Speed of detection derived from the speed of model execution is also important for earlier detection of fraudulent cases. …”
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Cluster optimization in VANET using MFO algorithm and K-Means clustering
Published 2023“…Proven to be an effective and efficient method for solving optimization problem. To design K-Means algorithm that portion nodes based on their proximities by optimize the distance between nodes within same cluster by assigning them to the closet cluster center. …”
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Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…Adopting the medoid instead of the mean can enhance the efficiency. However, the complexity of the kmedoid based algorithms in general is more than the complexity of the k-means based algorithms. …”
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17
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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A review on object detection algorithms based deep learning methods / Wan Xing ... [et al.]
Published 2023“…Deep learning-based object detection algorithms can be categorized into three main types: end-to-end algorithms, two-stage algorithms, and one-stage algorithms. …”
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Improved abnormal detection using self-adaptive social force model for visual surveillance
Published 2017“…In this work, we aim to find the significant interaction forces and detect the abnormality in the crowd by using Self-Adaptive Social Force Model. …”
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Fault section detection and location on distribution network using analytical voltage sags database
Published 2006“…This paper presents the application of voltage sags information for automatic fault section detection and location on a distribution network. Based on a network topology and load estimations obtained from load modeling, this method uses a three phase load flow and fault analysis to establish analytical voltage sags database information for a studied distribution network. …”
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