Search Results - (( time estimation using algorithm ) OR ( data distribution function algorithm ))

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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Some families of count distributions for modelling zero-inflation and dispersion / Low Yeh Ching by Low, Yeh Ching

“…A popular distribution for the modelling of discrete count data is the Poisson distribution. …”
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Rank regression for modeling bus dwell time in the presence of censored observations by Karimi, Mostafa, Ibrahim, Noor Akma

“…A resampling technique is used for estimating the distribution of the rank estimator through its empirical distribution. …”
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Automatic database of robust neural network forecasting / Saadi Ahmad Kamaruddin, Nor Azura Md. Ghani and Norazan Mohamed Ramli by Ahmad Kamaruddin, Saadi, Md. Ghani, Nor Azura, Mohamed Ramli, Norazan

“…Therefore, this automatic database is designed to provide an alternative for robust neural network forecasting using statistical robust estimators of M-estimators, Iterated Least Median Square (ILMedS) and Particle Swarm Optimization on Least Median Square (PSO-LMedS), replacing the MSE cost function to handle time series data with missing values, outliers and noise, which always exist in real-life-time series data. …”
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Variational Bayesian inference for exponentiated Weibull right censored survival data by Jibril Abubakar, Jibril Abubakar, Mohd Asrul Affendi Abdullah, Mohd Asrul Affendi Abdullah, Oyebayo Ridwan Olaniran, Oyebayo Ridwan Olaniran

“…The exponential, Weibull, log-logistic and lognormal distributions represent the class of light and heavy-tailed distributions that are often used in modelling time-to-event data. …”
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Non-Parametric and Parametric Estimations of Cure Fraction Using Right-and Interval-Censored Data by Aljawdi, Bader

“…In this case, the estimation was developed based on the exponential and Weibull distributions using the right and interval censoring types; and 2) when covariates were incorporated into the analysis through the scaleparameter of the exponential distribution only using the same types of data censoring. …”
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Parametric and Semiparametric Competing Risks Models for Statistical Process Control with Reliability Analysis by Mohamed Elfaki, Faiz Ahmed

“…A generated data where the failure times are taken as exponentially distributed are used to further compare these two parametric models. …”
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Robust Kernel Density Function Estimation by Dadkhah, Kourosh

“…The classical kernel density estimation technique is the commonly used method to estimate the density function. …”
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Predicting the popularity of tweets using the theory of point processes. by Tan, Wai Hong

“…The mode of the posterior distribution is used as the estimator of the finite-dimensional parameter, and suitable functionals of the predictive distribution for the number of retweets implied by the estimated model are used to predict the tweet popularity. …”
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Parameter estimation of Kumaraswamy Burr type X models based on cure models with or without covariates by Yusuf, Madaki Umar

“…In this thesis, we considered two methods via the classical maximum likelihood estimation (MLE) and the Bayes estimation using the Gibbs sampling (G-S) algorithm to estimate the parameters of BKBX, KBX and Beta-Weibull (BWB) models. …”
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Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar by Seyed Alireza, Ravanfar

“…To improve the proposed algorithm, GA was utilized to identify the best choice for ‘‘mother wavelet function” and “decomposition level” of the signals by means of the fundamental fitness function. …”
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ETERS: A comprehensive energy aware trust-based efficient routing scheme for adversarial WSNs by Khan, T., Singh, K., Hasan, M.H., Ahmad, K., Reddy, G.T., Mohan, S., Ahmadian, A.

“…ETERS utilizes the Beta distribution-based trust function because recovery of trust values under attacks is faster in Beta distribution than Gaussian and Dirichlet distribution. …”
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Density based subspace clustering: a case study on perception of the required skill by Rahmat Widia, Sembiring

“…In the early stage, the present research estimates density dimensions and the results are used as input data to determine the initial cluster based on density connection, using DBSCAN algorithm. …”
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Density subspace clustering: a case study on perception of the required skill by Sembiring, Rahmat Widia

“…In the early stage, the present research estimates density dimensions and the results are used as input data to determine the initial cluster based on density connection, using DBSCAN algorithm. …”
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Optimization of hydropower reservoir system using genetic algorithm for various climatic scenarios by Tayebiyan, Aida

“…By using the daily observed data, ANN can map the relationship between rainfall-runoff. …”
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Sizing and placement of battery-coupled distributed photovoltaic generations by Ali, A., Mohd Nor, N., Ibrahim, T., Fakhizan Romlie, M.

“…Mixed-integer optimization using a genetic algorithm is employed for solving the optimization problem. …”
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Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani by Ehsan Taslimi , Renani

“…In this method, firstly, Weibull density function is utilized to model the wind speed and then several methods are applied to estimate the parameters of the wind speed distribution. …”
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Efficiency of 4253HT smoothers in extracting signal from noise and their applications in forecasting by Khairol Azmi, Nurul Nisa'

“…The extracted signal was then used for better forecasting which was facilitated by seasonal Holt-Winters, ARAR and seasonal ARIMA algorithm.…”
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Skype multimedia application traffic analysis on home Unifi network / Siti Fatimah Ramle by Ramle, Siti Fatimah

“…Two parameter Cumulative Distributions Functions (CDF) is generated. Maximum Likelihood Estimator (MLE) technique is used to get the best traffic model which presents the highest MLE value. …”
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Fault Detection Relevant Modeling of an Industrial Gas Turbine based on Neuro-Fuzzy Approach by Alemu Lemma, Tamiru, Mohd Hashim, Fakhruldin, Rangkuti, Chalillullah

“…Structure and network weights for the NF model are determined by a synergetic approach – Data clustering and Gradient Descent algorithm. Operation data collected in 10 seconds interval and for one day is used for model training and validation. …”
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