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

An improved bat algorithm with artificial neural networks for classification problems by Rehman Gillani, Syed Muhammad Zubair

“…ABC, HS, CS, WS, BPNN, LM, and ERNN etc.). Recently, a new metaheuristic search Bat algorithm has become quite popular due its tendency towards convergence to optimal points in the search trajectory by using echo-location behavior of bats as its random walk. …”
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Estimation Of Weibull Parameters Using Simulated Annealing As Applied In Financial Data by Hamza, Abubakar

“…However, the selection of the most suitable estimators is still a challenging task. The present study proposes a simulated annealing algorithm (SA) in estimating the parameters of Weibull distribution with application to modified internal rate of return data (MIRR).The objective is to examine the investment potential of the shari’ah compliance companies of the Malaysia property sector (MPS). …”
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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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An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli by Mohammed Adam, Kunna, Tuty Asmawaty, Abdul Kadir, Muhammad Akmal, Remli, Noorlin, Mohd Ali, Kohbalan, Moorthy, Noryanti, Muhammad

“…In addition, building a kinetic model requires the estimation of the kinetic parameters, but kinetic parameters estimation in kinetic modeling is a difficult task due to the nonlinearity of the model. …”
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Improved performance in distributed estimation by convex combination of DNSAF and DNLMS algorithms by Ahmad Pouradabi, Amir Rastegarnia, Azam Khalili, Ali Farzamnia

“…In diffusion estimation of distributed networks two characteristic parameters are crucial, the speed of convergence and steady-state error. …”
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Prior selection for Gumbel distribution parameters using multiple-try metropolis algorithm for monthly maxima PM10 data by Mohd Amin, Nor Azrita, Adam, Mohd Bakri, Ibrahim, Noor Akma

“…The main objective is to explore the accuracy of the parameter estimation to the change of priors and compare the results with a classical likelihood-based analysis. …”
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An improved dynamic load balancing for virtualmachines in cloud computing using hybrid bat and bee colony algorithms by Ullah, Arif

“…Therefore, to overcome these problems, this study proposed an improved dynamic load balancing technique known as HBAC algorithm which dynamically allocates task by hybridizing Artificial Bee Colony (ABC) algorithm with Bat algorithm. …”
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Accuracy enhancement for zone mapping of a solar radiation forecasting based multi-objective model for better management of the generation of renewable energy by Ehteram M., Ahmed A.N., Fai C.M., Afan H.A., El-Shafie A.

“…Air quality; Decision making; Forecasting; Fuzzy inference; Fuzzy neural networks; Fuzzy systems; Genetic algorithms; Inference engines; Mapping; Mean square error; Multiobjective optimization; Optimal systems; Particle swarm optimization (PSO); Quality control; Renewable energy resources; Solar radiation; Uncertainty analysis; Adaptive neuro-fuzzy inference system; ANFIS; Multi objective algorithm; Multi objective particle swarm optimization; Multi-objective genetic algorithm; Renewable energies; Renewable energy generation; Solar radiation forecasting; Parameter estimation…”

Kalman filter based impedance parameter estimation for transmission line and distribution line by Siti Nur Aishah, Mohd Amin

“…Therefore, a detailed study on developing and evaluating the new algorithms for transmission line parameter estimation is considered in this thesis. …”
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Estimation of Transformers Health Index Based on Condition Parameter Factor and Hidden Markov Model by Selva A.M., Yahaya M.S., Azis N., Ab Kadir M.Z.A., Jasni J., Yang Ghazali Y.Z.

“…Electric transformers; Health; Hidden Markov models; Nonlinear programming; Probability distributions; Quality control; Viterbi algorithm; Condition parameters; Dissolved gas analysis; Distribution transformer; Emission probabilities; Health indices; Non-linear optimization; Remaining useful lives; Transition probabilities; Parameter estimation…”

Slice sampler algorithm for generalized pareto distribution by Rostami, Mohammad, Adam, Mohd Bakri, Yahya, Mohamed Hisham, Ibrahim, Noor Akma

“…Moreover, the slice sampler algorithm presents a higher level of stationarity in terms of the scale and shape parameters compared with the Metropolis-Hastings algorithm. …”
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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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Evaluation of lightning current parameters using measured lightning induced voltage on distribution power lines by Izadi M., Kadir M.Z.A.A., Osman M.

“…Electromagnetic fields; Parameter estimation; Channel base current; Electromagnetic field components; Lightning current parameters; Lightning induced voltage; Lightning location; Lightning location systems; Overhead distribution line; Performance of algorithm; Lightning…”

A parametric mixture model of three different distributions: An approach to analyse heterogeneous survival data by Mohammed, Yusuf Abbakar, Yatim, Bidin, Ismail, Suzilah

“…A parametric mixture model of three different distributions is proposed to analyse heterogeneous survival data.The maximum likelihood estimators of the postulated parametric mixture model are estimated by applying an Expectation Maximization Algorithm (EM) scheme.The simulations are performed by generating data, sampled from a population of three component parametric mixture of three different distributions. …”
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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

“…A new self-adaptive hybrid algorithm (CSCMAES) is introduced for optimization. …”
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Parameter-driven count time series models / Nawwal Ahmad Bukhari by Nawwal , Ahmad Bukhari

“…Simulation shows that MCEM algorithm and particle method are useful for the parameter estimation of the Poisson model. …”
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Voltage and load profiles estimation of distribution network using independent component analysis / Mashitah Mohd Hussain by Mohd Hussain, Mashitah

“…First, voltage profile on source distribution system is estimated. The voltage profile is predicted using Independent Component Analysis (lCA) algorithm. …”
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Short circuit power based fault location algorithm in distribution networks by Farzan, Payam, Izadi, Mahdi, Gomes, Chandima, Ab Kadir, Mohd Zainal Abidin, Hesamian, Mohammad Hesam, Mohd Radzi, Mohd Amran

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Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares by Uraibi, Hassan Sami

“…The Ordinary Least Squares (OLS) method is often used to estimate the parameters of a linear model. Under certain assumptions, the OLS estimates are the best linear unbiased estimates. …”
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Applying non-informative G-prior for logistic regression models with different patterns of data points by Pham, Huong T.T., Pham, Hoa, Siong Yow, Kai

“…In the Bayesian approach, the existence of posterior means is also affected by the presence of separation depending on the form of prior distributions. In this paper, a non-informative G-prior for Bayesian method is proposed to reduce the bias of the parameter estimation when prior distributions of parameters do not have information and separation is present in the data. …”
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