Search Results - (( a distribution process algorithm ) OR ( (parameter OR parameters) estimation means algorithm ))
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Parameter-driven count time series models / Nawwal Ahmad Bukhari
Published 2018“…Simulation shows that MCEM algorithm and particle method are useful for the parameter estimation of the Poisson model. …”
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Application of image processing and adaptive neuro-fuzzy system for estimation of the metallurgical parameters of a flotation process
Published 2016“…The authors have already developed some reliable algorithms for measurement of the froth surface visual parameters such as bubble size distribution, froth color, velocity and stability. …”
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Air quality measurement using remote sensing and digital images processing techniques / Lim, H. S. … [et al.]
Published 2004“…The newly developed algorithm produced a high degree of accuracy with the correlation coefficient (R) of 0.9001 and the root-mean-square error (RMS) of 5.1008 µg/m³ for PM10. …”
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A generator of cauchy-distributed time series with specific Hurst index
Published 2011“…The proposed algorithm consists of an inverse cumulative distribution function (ICDF) transformation, a wavelet-analysis synthesis and, finally, a linear transformation. …”
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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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Covariance matrix analysis in simultaneous localization and mapping
Published 2016“…In mobile robot SLAM, extended Kalman filter (EKF) has been one of the most preferable estimators due to its relatively simple algorithm and efficiency of the estimation through the representation of the belief by a multivariate Gaussian distribution; unimodal distribution, with a single mean annotated with a corresponding covariance uncertainty. …”
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Statistical modelling of time series of counts for a new class of mixture distributions / Khoo Wooi Chen
Published 2016“…The iv score functions and information matrix have been derived to measure the asymptotic standard errors and to analyze the variance-covariance relationship among the parameters. Parameter estimation with the maximum likelihood estimation via the Expectation-Maximization algorithm is discussed and compared with the conditional least squares method. …”
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Parametric and Semiparametric Competing Risks Models for Statistical Process Control with Reliability Analysis
Published 2004“…The Expectation Maximization (EM) algorithm is utilized to obtain the estimate of the parameters in the models. …”
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Channel Modeling and Direction-of-Arrival Estimation in Mobile Multiple-Antenna Communication Systems
Published 2005“…The second part of the thesis deals with channel parameter estimation of distributed scattering sources. …”
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Extreme air pollutant data analysis using classical and Bayesian approaches
Published 2015“…MTM algorithm is an extension of MH algorithm, designed to improve the convergence of MH algorithm by performing parallel computation. …”
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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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A comparative study of evolutionary algorithms and adapting control parameters for estimating the parameters of a single-diode photovoltaic module's model
Published 2023“…Algorithms; Diodes; Errors; Iterative methods; Least squares approximations; Mean square error; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Coefficient of determination; Differential Evolution; Electromagnetism-like algorithm; Hybrid evolutionary algorithm; Photovoltaic; Photovoltaic modules; Root mean square errors; Single-diode models; Evolutionary algorithms; algorithm; comparative study; electromagnetic method; estimation method; experimental design; numerical method; parameterization; performance assessment; photovoltaic system…”
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An Improved Scatter Search Algorithm for Parameter Estimation in Large-Scale Kinetic Models of Biochemical Systems
Published 2019“…Methods: This paper proposes an improved scatter search algorithm to address the challenging parameter estimation problem. …”
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An improved scatter search algorithm for parameter estimation in large-scale kinetic models of biochemical systems
Published 2019“…Methods: This paper proposes an improved scatter search algorithm to address the challenging parameter estimation problem. …”
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Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems
Published 2011“…The main idea is the integration of optimal control and parameter estimation. In this work, a simplified model-based optimal control model with adjustable parameters is constructed. …”
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Estimation Of Weibull Parameters Using Simulated Annealing As Applied In Financial Data
Published 2023“…The performance of the SA algorithm has been explored in terms of accuracies and estimation errors. …”
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MULTIVARIABLE CLOSED-LOOP SYSTEM IDENTIFICATION USING ITERATIVE LEAKY LEAST MEAN SQUARES METHOD
Published 2017“…In this research. novel algorithms have been developed to: (I) isolate the less interacting channe Is using a modified partial correlation algorithm. (2) achieve unbiased and consistent parameter estimates using an iterative LLMS algorithm and (3) develop parsimonious models for closed-loop MIMO systems. …”
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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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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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