Search Results - (( parameter estimation clustering algorithm ) OR ( variable detection sensor algorithm ))
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1
Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach
Published 2022“…The most popular method to solve parameter estimation problem is using optimization algorithm that easily trap to local minima and poor in exploitation to find the good solutions. …”
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2
Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor
Published 2017“…As for the multiple outliers, a clustering algorithm is considered and a dendogram to visualise the clustering algorithm is used. …”
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3
Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari
Published 2015“…We derive the maximum likelihood estimation of parameters as well as the variance-covariance of parameters. …”
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4
Parameter estimation of K-distributed sea clutter based on fuzzy inference and Gustafson-Kessel clustering
Published 2011“…This paper proposes a novel approach to estimate the parameters of K-distribution, based on fuzzy Gustafson–Kessel clustering and fuzzy Takagi–Sugeno Kang modelling. …”
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5
A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. Then, the developed algorithm is implemented to estimate the parameters of the Lorenz system. …”
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6
Observer-based fault detection with fuzzy variable gains and its application to industrial servo system
Published 2020“…Also, a scoring algorithm has been implemented, to evaluate the classification ability of the algorithm and the early fault detection ability. …”
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7
An investigation of structural breaks on spot and futures crude palm oil returns
Published 2011“…In contrast to the spot crude palm oil findings, the futures crude palm oil exhibits a lower persistency estimation when structural changes are considered. The results support the importance of structural breaks in this volatility clustering estimation, and failure to do so may lead to bias persistency parameter estimation.…”
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8
Semiparametric binary model for clustered survival data
Published 2014“…We investigated the effects of the strength of cluster correlation and censoring rates on properties of the parameters estimate. …”
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9
Expectation maximization clustering algorithm for user modeling in web usage mining system
Published 2009“…The model is based on expectation-maximization (EM) algorithm and it is used for finding maximum likelihood estimates of parameters in probabilistic models, where the model depends on unobserved latent variables. …”
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10
The multiple outliers detection for circular univariate data using different agglomerative clustering algorithms
Published 2024“…In univariate circular data, the presence of outliers is acclaimed will affect the parameter estimates and inferences. This study proposes the procedure of detecting multiple outliers, particularly for univariate circular data based on agglomerative clustering algorithms. …”
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11
Deforestation detection in Kinabalu Area, Sabah, Malaysia by using multi-sensor remote sensing approach
Published 2004“…This paper examines use of multi-sensor remote sensing approach for deforestation detection in the tropics. …”
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12
Kernel and multi-class classifiers for multi-floor wlan localisation
Published 2016“…The multi-class classification strategy is used to ensure quick estimation of the multi-class NN algorithms. All of the algorithms are later combined to provide device location estimation for multi-floor environment. …”
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13
Algorithm enhancement for host-based intrusion detection system using discriminant analysis
Published 2004“…Misuse detection algorithms model know attack behavior. They compare sensor data to attack patterns learned from the training data. …”
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14
Individual-tree segmentation and extraction based on LiDAR point cloud data
Published 2024“…In the task of individual tree extraction, the point cloud distance discriminant clustering algorithm outperformed the watershed algorithm. …”
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15
A study on advanced statistical analysis for network anomaly detection
Published 2005“…Misuse detection algorithms model know attack behavior. They compare sensor data to attack patterns learned from the training data. …”
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16
Cluster head selection using fuzzy logic and chaotic based genetic algorithm in wireless sensor network
Published 2013“…Wireless sensor networks (WSNs) are composed of hundreds or thousands of sensor nodes in order to detect and transmit information from its surrounding environment. …”
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17
Modelling and analysis of sensor fault tolerant control using behavioral approach to systems theory
Published 2015“…State observers are then implemented as the fault detection method in which the discrepancies between the measured values by the sensors and the values of the model are expressed as residuals. …”
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18
DESIGN OF SMART TRAFFIC LIGHT SYSTEM BASED ON INTERNET OF THINGS
Published 2018“…Density of the traffic is calculated by the algorithm that have various variables. This project will use Arduino as it microcontroller and the ultrasonic is used to detect the congestion. …”
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Multi-sensor fusion and deep learning framework for automatic human activity detection and health monitoring using motion sensor data / Henry Friday Nweke
Published 2019“…This is further worsen by the use of single sensors modality and machine learning algorithms. …”
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20
Machine learning for mapping and forecasting poverty in North Sumatera: a datadriven approach
Published 2024“…The best model was created using the grid search cross-validation, while the best prediction results were created using the RF algorithm, with the following parameters: n-estimator = 50, max depth = 10, min samples split = 2, and min samples leaf = 1. …”
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