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Semiparametric inference procedure for the accelarated failure time model with interval-censored data
Published 2019“…The rank-based methods, estimating algorithms, and resampling techniques that are developed do not involve the difficulties of the existing estimating procedures. …”
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2
Simulation algorithm of bayesian approach for choice-conjoint model
Published 2011“…Therefore this research propose simulation algorithm of Bayesian approach for estimating parameter in MPM by Bayesian analysis to avoid computational difficulties in computing the maximum likelihood estimates (MLE).…”
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3
The research on the signal source number estimation algorithm
Published 2024“…The experimental results show that with the increase of the SNR and the number of array elements, the correct estimation probability of the algorithm also increases correspondingly, which provides a reliable experimental basis and performance evaluation for the estimation. © 2024 Institute of Advanced Engineering and Science. …”
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Tree-based contrast subspace mining method
Published 2020“…Then, the tree-based method, the genetic algorithm based parameter values identification of tree-based method, and followed by the genetic algorithm based tree-based method, for numerical data sets are developed and evaluated. …”
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Estimation of Transformers Health Index Based on Condition Parameter Factor and Hidden Markov Model
Published 2023Conference Paper -
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…These algorithms are inspired by the estimation capability of the well-known Kalman filter estimation method. …”
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7
Comparison between Newton’s Method and a new Scaling Newton Method / Ramizah Baharuddin
Published 2021“…Newton's Method also called the Newton-Raphson method is a recursive algorithm for approximating the root of a differentiable function. …”
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8
Outlier detection in circular regression model using minimum spanning tree method
Published 2019“…The existence of outliers in a circular regression model can lead to many errors, for example in inferences and parameter estimations. Therefore, this study aims to develop new algorithms that can detect outliers by using the minimum spanning tree method. …”
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Color Image Segmentation Based on Bayesian Theorem for Mobile Robot Navigation
Published 2009“…The estimation of unknown PDF is a common problem and in this study Gaussian kernel function which is most widely used nonparametric density estimation method has been used for PDF calculation. …”
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11
Robust estimation methods for fixed effect panel data model having block-concentrated outliers
Published 2019“…The Ordinary Least Squares (OLS) is the commonly used method to estimate the parameters of fixed effect panel data model. …”
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12
Neighbour-based on-demand routing algorithms for mobile ad hoc networks
Published 2017“…Accordingly, a Novel Density-Aware Routing algorithm (NDAR) is proposed. The proposed algorithm totally eliminates the need for fixed threshold values through the use of a novel formula that can easily estimate the node density and replace the fixed threshold value based on the neighbor information. …”
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13
Estimation of transformers health index based on condition parameter factor and hidden Markov model
Published 2018“…Next, the emission probabilities for each of the condition parameter factors were derived based on frequency of occurrence method. …”
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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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Scale-invariant and adaptive-search template matching for monocular visual odometry in low-textured environment
Published 2016“…This method is one of the most effective methods for template matching. …”
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Identification of hammerstain model using stochastic perturbation simultaneous approximation
Published 2016“…A numerical example is given to illustrate that the SPSA based algorithms can give accurate parameter estimate of the Hammerstein models with high probability through detailed simulation.…”
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Undergraduates Project Papers -
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Robust Kernel Density Function Estimation
Published 2010“…The classical kernel density estimation technique is the commonly used method to estimate the density function. …”
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Particle swarm optimization for NARX structure selection application on DC motor model: article / Mohd I. Abdullah
“…This paper presents the nonlinear identification of a DC motor using Binary Particle Swarm Optimization (BPSO) algorithm, as a model structure selection method, replacing the typical Orthogonal Least Squares (OLS) used in system identification. …”
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