Search Results - parameter estimation ((((using algorithm) OR (matching algorithm))) OR (clustering algorithm))
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1
Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence
Published 2011“…Block-matching algorithm is the most common technique applied in block-based motion estimation technique. …”
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Book Chapter -
2
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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3
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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Thesis -
4
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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5
Combining Recursive Least Square and Principal Component Analysis for Assisted History Matching
Published 2014“…Currently not much attention is given for using RLS for history matching purposes. Even though RLS is a simple and effective method to estimate parameters, RLS have stability problem when number of parameters is high. …”
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Final Year Project -
6
An Improved Hybrid of Particle Swarm Optimization and the Gravitational Search Algorithm to Produce a Kinetic Parameter Estimation of Aspartate Biochemical Pathways
Published 2017“…The results show that the proposed algorithm outperformed other standard optimization algorithms in terms of accuracy and near-optimal kinetic parameter estimation. …”
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7
Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari
Published 2015“…Here, we introduce a measure of similarity based on the circular distance and obtain a cluster tree using the single linkage clustering algorithm. …”
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Thesis -
8
The multiple outliers detection for circular univariate data using different agglomerative clustering algorithms
Published 2024“…Three circular similarity measures are used to obtain the dendrogram from three agglomerative clustering algorithms. …”
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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
SKF-based image template matching for distance measurement by using stereo vision
Published 2018“…The traditional algorithm to solve image matching problem take a lot of memory and computational time. …”
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Book Chapter -
11
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. …”
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Thesis -
12
Application of Evolutionary Algorithm for Assisted History Matching
Published 2014“…Besides, algorithm based method has been widely used to forecast future result in various field for example art, biology, marketing including engineering. …”
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Final Year Project -
13
Arabic words recognition technique for pattern matching using SIFT, SURF and ORB
Published 2017“…A parameters estimator of models algorithm is used to weed out the outlier point of matching images. …”
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Article -
14
Parameter estimation of K-distributed sea clutter based on fuzzy inference and Gustafson-Kessel clustering
Published 2011“…This is achieved by a pre-estimation using fuzzy clustering that provides a prior knowledge and forms a rough model to be fine tuned using the least square method. …”
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15
An investigation of structural breaks on spot and futures crude palm oil returns
Published 2011“…Having identified the breaks in the mean and variance of both returns series, we model their relationship by incorporating those breaks in the volatility clustering procedure (using modified BEKK model). The volatility clustering finding show that the spot crude palm oil persistency parameters have slightly increased when structural breaks are taken into account in the estimated model. …”
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16
Semiparametric binary model for clustered survival data
Published 2014“…A backfitting algorithm is used in the derivation of the estimating equation for the parametric and nonparametric components of a semiparametric binary covariate model. …”
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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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19
Codebook excited linear predictive coding
Published 2011“…Because ofthe limitations ofthe coding build blocks the estimated filter parameters case as the estimation errors in a result speech quality suffers degradations. …”
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Book Chapter -
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