Search Results - (( _ distribution some algorithm ) OR ( parameter estimation ((a algorithm) OR (new algorithm)) ))

Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari by Satari, Siti Zanariah

“…This study focuses on the parameter estimation and outlier detection for some types of the circular model. …”
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Some families of count distributions for modelling zero-inflation and dispersion / Low Yeh Ching by Low, Yeh Ching

“…For parameter estimation, the simulated annealing global optimization routine and an EM-algorithm type approach for maximum likelihood estimation are studied. …”
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Statistical modelling of time series of counts for a new class of mixture distributions / Khoo Wooi Chen by Khoo, Wooi Chen

“…The statistical and regression properties, parameter estimation, forecasting, and graphical analysis for the new model have been examined. …”
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Semiparametric inference procedure for the accelarated failure time model with interval-censored data by Karimi, Mostafa

“…A computationally simple two-step iterative algorithm, called estimationapproximation algorithm, is introduced for estimating the parameters of the model on the basis of the rank estimators. …”
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A new metaphor-less algorithms for the photovoltaic cell parameter estimation by Premkumar M., Babu T.S., Umashankar S., Sowmya R.

A simulation study of a parametric mixture model of three different distributions to analyze heterogeneous survival data by Mohammed, Yusuf Abbakar, Yatim, Bidin, Ismail, Suzilah

“…In this paper a simulation study of a parametric mixture model of three different distributions is considered to model heterogeneous survival data.Some properties of the proposed parametric mixture of Exponential, Gamma and Weibull are investigated.The Expectation Maximization Algorithm (EM) is implemented to estimate the maximum likelihood estimators of three different postulated parametric mixture model parameters.The simulations are performed by simulating data sampled from a population of three component parametric mixture of three different distributions, and the simulations are repeated 10, 30, 50, 100 and 500 times to investigate the consistency and stability of the EM scheme.The EM Algorithm scheme developed is able to estimate the parameters of the mixture which are very close to the parameters of the postulated model.The repetitions of the simulation give parameters closer and closer to the postulated models, as the number of repetitions increases, with relatively small standard errors.…”
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Finite impulse response optimizers for solving optimization problems by Ab Rahman, Tasiransurini

“…In this work, three new estimation-based metaheuristic algorithms are introduced. …”
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Finite impulse response optimizers for solving optimization problems by Tasiransurini, Ab Rahman

“…In this work, three new estimation-based metaheuristic algorithms are introduced. …”
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LASSO-type estimations for threshold autoregressive and heteroscedastic time series models. by Muhammad Jaffri Mohd Nasir

“…A new algorithm of coordinate gradient descent (CGD) is developed to optimize the adaptive LASSO. …”
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Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh by Rawaa Dawoud Hassan, Al-Dabbagh

“…ARDE is also used to develop a new dynamic parameter identification framework to estimate the barycentric parameters of the CRS A456 robot manipulator. …”
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Dynamic robust bootstrap method based on LTS estimators by Midi, Habshah, Uraibi, Hassan Sami, Al-Talib, Bashar Abdul Aziz Majeed

“…The applications of bootstrap methods in regression analysis have drawn much attention to the statistics practitioners because of some practical reasons. In order to make reliable inferences about the parameters of a model, require that the parameter estimates are normally distributed. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…The first research objective is to develop a new deep learning algorithm by a hybrid of DNN and K-Means Clustering algorithms for estimating the Lorenz chaotic system. …”
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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 by Muhsen D.H., Ghazali A.B., Khatib T., Abed I.A.

Identifying and estimating solar cell parameters using an enhanced slime mould algorithm by Logeswaary, Devarajah, Mohd Ashraf, Ahmad, Jui, Julakha Jahan

“…This study proposed an enhanced slime mould algorithm (ESMA) for identifying the solar cells’ parameters for five photovoltaic (PV) models, making two modifications to the original slime mould algorithm (SMA). …”
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A new robust computational approach for the electric power system parameters by Khan, Z., Razali, R.B., Daud, H., Nor, N.M., Firuzabad, M.F., Krebs, K.L.

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Simulated Kalman Filter: A Novel Estimation-based Metaheuristic Optimization Algorithm by Zuwairie, Ibrahim, Nor Hidayati, Abd Aziz, Nor Azlina, Ab. Aziz, Saifudin, Razali, Mohd Saberi, Mohamad

“…This new algorithm is inspired by the estimation capability of the Kalman Filter. …”
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Fitness-guided particle swarm optimization with adaptive Newton-Raphson for photovoltaic model parameter estimation by Premkumar M., Ravichandran S., Hashim T.J.T., Sin T.C., Abbassi R.

Parameter estimation of multivariable system using Fuzzy State Space Algorithm / Razidah Ismail … [et al.] by Ismail, Razidah, Ahmad, Tahir, Harish, Noor Ainy, A. Halim, Rosenah

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Feature Selection and Classifier Parameter Estimation for Egg Signal Peak Detection using Gravitational Search Algorithm by Zuwairie, Ibrahim, Mohd Zaidi, Mohd Tumari, Asrul, Adam, Norrima, Mokhtar, Marizan, Mubin, Mohd Ibrahim, Shapiai

“…This study focuses on using GSA method, a new computational intelligence algorithm. Moreover, a rule-based classifier is employed to distinguish a peak point based on the selected features. …”
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Parameter extraction of photovoltaic module using hybrid evolutionary algorithm by Muhsen D.H., Ghazali A.B., Khatib T.