Search Results - (( parameter simulation based algorithm ) OR ( data detection using algorithm ))
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1
Comparative study of clustering-based outliers detection methods in circular-circular regression model
Published 2021“…Application to real data using wind data and a simulated data set are given for illustrative purposes. …”
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Comparative study of clustering-based outliers detection methods in circular-circular regression model
Published 2021“…Application to real data using wind data and a simulated data set are given for illustrative purposes. …”
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3
Comparative study of clustering-based outliers detection methods in circularcircular regression model
Published 2021“…Application to real data using wind data and a simulated data set are given for illustrative purposes. …”
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4
The multiple outliers detection for circular univariate data using different agglomerative clustering algorithms
Published 2024“…This study proposes the procedure of detecting multiple outliers, particularly for univariate circular data based on agglomerative clustering algorithms. …”
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5
Reduced rank technique for joint channel estimation and joint data detection in TD-SCDMA systems
Published 2013“…We exploit the rank deficient of H to reduce the number of parameters that characterizes this matrix. The adopted reduced rank technique is based on singular value decomposition algorithm. …”
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Fraud detection in telecommunication using pattern recognition method / Mohd Izhan Mohd Yusoff
Published 2014“…The new algorithm is tested on simulated and real data where the results show it is capable of detecting fraud activities. …”
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7
Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari
Published 2015“…Lastly, we consider the problem of detecting multiple outliers in circular regression models based on the clustering algorithm. …”
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Reduced Rank Technique for Joint Channel Estimation and Joint Data Detection in TD-SCDMA Systems
Published 2012“…We exploit the rank deficient of H to reduce the number of parameters that characterizes this matrix. The adopted reduced rank technique is based on singular value decomposition algorithm. …”
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10
Road damage detection for autonomous driving vehicles using YOLOv8 and salp swarm algorithm
Published 2025“…The model is trained using the Czech data in Road Damage Dataset RDD2022 from the Crowdsensing-based Road Damage Detection Challenge (CRDDC’2022), with 80% of the data used for training and 20% for validation. …”
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Detection of black hole nodes in mobile ad hoc network using hybrid trustworthiness and energy consumption techniques
Published 2017“…In this thesis, a hybrid detection algorithm mechanism has been proposed which combines two detection algorithms based on nodes’ trustworthiness and energy consumption in a parallel manner in order to detect the black hole nodes. …”
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Sequence and sequence-less t-way test suite generation strategy based on the elitist flower pollination algorithm
Published 2018“…Interaction, or t-way, testing, where t indicates the interaction strength, is an approach to generate test suite for detecting fault due to interaction. In line with the emerging field called Search based Software Engineering, many recently developed t-way strategies have adopted meta-heuristic algorithms as the basis of their implementations such as Simulated Annealing, Genetic Algorithm, Ant Colony Optimization Algorithm, Particle Swarm Optimization, Harmony Search and Cuckoo Search, owing their superior performance in term of test size reduction as compared to general computational based strategies, such as General t-way, Test Vector Generator, In Parameter Order General, Jenny, and Automatic Efficient Test Generator. …”
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Defect recognition method for magnetic leakage detection in oil and gas steel pipes based on improved neural networks / Wang Jie ... [et al.]
Published 2024“…Traditional BP networks face challenges, including parameter determination and slow convergence, addressed through genetic algorithms' global search capabilities. Simulated data are generated using ANSYS software by using models of semi-circular defects in steel pipes, producing magnetic leakage signals of varying intensities. …”
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Defect recognition method for magnetic leakage detection in oil and gas steel pipes based on improved neural networks
Published 2024“…Traditional BP networks face challenges, including parameter determination and slow convergence, addressed through genetic algorithms' global search capabilities. Simulated data are generated using ANSYS software by using models of semi-circular defects in steel pipes, producing magnetic leakage signals of varying intensities. …”
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Vision-Based Autonomous Vehicle Driving Control System
Published 2005“…The important contribution of this study is the development of vehicle lane detection and tracking algorithm based on colour cue segmentation, Canny edge detection and Hough transform. …”
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Vision-based autonomous vehicle driving control system
Published 2005“…The important contribution of this study is the development of vehicle lane detection and tracking algorithm based on colour cue segmentation, Canny edge detection and Hough transform. …”
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17
Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares
Published 2009“…To rectify this problem, we propose a Dynamic Robust Bootstrap-LTS based (DRBLTS) algorithm where the percentage of outliers in each bootstrap sample is detected. …”
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18
Embedded fuzzy classifier for detection and classification of preseizure state using real EEG data
Published 2014“…The algorithm also utilizes certain statistical features from the EEG signal that are used as features to the classifier logic. …”
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19
Reduced-rank technique for joint channel estimation in TD-SCDMA systems.
Published 2013“…We exploit the rank deficient of H to reduce the number of parameters that characterizes this matrix. The adopted reduced rank technique is based on singular value decomposition algorithm. …”
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Parameter estimation of multicomponent transient signals using deconvolution and ARMA modelling techniques
Published 2003“…Using an autoregressive moving (ARMA) model whose AR parameters are determined by solving high-order Yule-Walker equations (HOYWE) via the singular value decomposition (SVD) algorithm can alleviate this shortcoming. …”
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