Search Results - (( time estimation methods algorithm ) OR ( a distribution function algorithm ))*

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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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 family of count distributions, which is able to model under- and over dispersion, is presented by considering the inverse Gaussian distribution, the convolution of two gamma distributions and a finite mixture of exponential distributions as the distribution of the inter-arrival times. …”
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Parameter estimation in computational systems biology models: a comparative study of initialization methods in global optimization by Muhammad Akmal, Remli, Nor Syahidatul Nadiah, Ismail, Noor Azida, Sahabudin, Nor Bakiah, Abd Warif

“…Global optimization method based on an enhanced scatter search (ESS) algorithm is a suitable choice to address this issue. …”
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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

“…The direct idea of making the conventional neural network learning algorithm more powerful towards outlying data is by replacing the mean square error (MSE) with a different symmetric and continuous cost function. …”
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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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Non-Parametric and Parametric Estimations of Cure Fraction Using Right-and Interval-Censored Data by Aljawdi, Bader

“…This research investigated the non-parametric maximum likelihood estimation method for cure rate estimation by considering two common estimators for the survival function: 1) The Kaplan Meier (KM) estimator, which is suitable for the right censoring case; and 2) The Turnbull Estimator, which is suitable for the interval type of data censoring. …”
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Parameter estimation of Kumaraswamy Burr type X models based on cure models with or without covariates by Yusuf, Madaki Umar

“…Further-more, one of the weakness of Beta distribution is that it is not fairly tractable and in a particular case, its cumulative distribution function (CDF) involves the incomplete beta function ratio. …”
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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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Sensorless Adaptive Fuzzy Logic Control Of Permanent Magnet Synchronous Motor by Hafz Nour, Mutasim Ibrahim

“…Both experimental and simulation results obtained from the HMRASC and the position angle estimation algorithms showed superior results compared to other methods presented in the literature.…”
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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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Power lines vegetation enchroachment monitoring based on satellite stereo images using stereo matching by Qayyum A., Malik A.S., Saad M.N.M., Iqbal M., Abdullah M.F., Abdullah T.A.R.B.T., Ramli A.Q.

“…In this paper,a new method based estimating 3D height/depth of vegetation or trees near transmission lines using satellite stereo vision is proposed. …”

Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar by Seyed Alireza, Ravanfar

“…Therefore, a new reference-free damage detection algorithm is proposed. …”
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Tumor Extraction for Brain Magnetic Resonance Imaging Using Modified Gaussian Distribution by Salih Al-Badri, Qussay Abbas

“…The mutual information algorithms used in this work has been developed and experimented in the system and has proven to yield more accurate and stable results than other algorithms. …”
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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

“…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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An Optimal Load Shedding Methodology for Radial Power Distribution Systems to Improve Static Voltage Stability Margin using Gravity Search by Khamis, Aziah

“…In this paper, an effective method is presented for estimating the optimal amount of load to be shed in a distribution system based on the gravitational search algorithm (GSA). …”
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Advanced Multiple Access Schemes for Multimedia Traffic over Wireless Channels by Habaebi, Mohamed Hadi

“…We propose scheduling algorithms for CBR, VBR and ABR traffic. Furthermore, we also introduce a method to dynamically adjust the number of uplink control slots per frame as a function of the estimated contention traffic. …”
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Fault diagnosis in unbalanced radial distribution networks using generalised regression neural network by Mirzaei, Maryam

“…Nowadays, about 80% of interruptions are caused by faults in distribution networks and the application of fault location algorithms developed for transmission system is not an easy task due to the topology and operating principles of the distribution networks. …”
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Density based subspace clustering: a case study on perception of the required skill by Rahmat Widia, Sembiring

“…The researches started with the problem were there are hidden data in a different space. Meanwhile the dimensionality increases, the farthest neighbour of data point expected to be almost as close as nearest neighbour for a wide range of data distributions and distance functions. …”
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Density subspace clustering: a case study on perception of the required skill by Sembiring, Rahmat Widia

“…The researches started with the problem were there are hidden data in a different space. Meanwhile the dimensionality increases, the farthest neighbour of data point expected to be almost as close as nearest neighbour for a wide range of data distributions and distance functions. …”
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