Search Results - (( data distribution function algorithm ) OR ( processes evaluation means algorithm ))

An experience oriented-convergence improved gravitational search algorithm for minimum variance distortionless response beamforming optimum by Darzi S., Tiong S.K., Tariqul Islam M., Rezai Soleymanpour H., Kibria S.

Geometric feature descriptor and dissimilarity-based registration of remotely sensed imagery by Kahaki S.M.M., Arshad H., Nordin M.J., Waidah Ismail

Enhanced Cuckoo Search Algorithm With Metaheuristic Components For Extracting The Maxima Of The Orientation Distribution Function by Shehab, Mohammad Mohammad Said

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Hierarchical Bayesian estimation for stationary autoregressive models using reversible jump MCMC algorithm by Suparman, S., Rusiman, Mohd Saifullah

“…In the hierarchical Bayesian approach, the order and coefficients of the autoregressive model are assumed to have a prior distribution. The prior distribution is combined with the likelihood function to obtain a posterior distribution. …”
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Modeling and Analysis of New Hybrid Clustering Technique for Vehicular Ad Hoc Network by Abdulrazzak H.N., Hock G.C., Mohamed Radzi N.A., Tan N.M.L., Kwong C.F.

“…The evaluation process was implemented on RK-Means, K-Means++, and OK-Means models. …”

Segmentation of MRI brain images using statistical approaches by Balafar, Mohammad Ali

“…Moreover, three improvements of EM for brain MRI segmentation are proposed, which incorporate neighbourhood information in a new manner in the clustering process. In addition, two algorithms for the post-processing of clustering results using user-interaction and the re-evaluation of boundary data in each cluster are presented. …”
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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

“…Thereafter, a multi-objective hybrid algorithm (MOHA), an extension of the self-adaptive hybrid algorithm is proposed and tested on the established multi-objective (MO) test functions. …”
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A new Gompertz-three-parameter-lindley distribution for modeling survival time data by Liang, Fei, Lu, Hezhi, Xi, Yuhang

“…The statistical properties of the proposed distribution including the shape properties, cumulative distribution, quantile functions, moment generating function, failure rate function, mean residual function, and stochastic orders are studied. …”
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Reliability Analysis and Prediction of Time to Failure Distribution of an Automobile Crankshaft by Salvinder Singh, Karam Singh, Shahrum, Abdullah, Nik Abdullah, Nik Mohamed

“…The developed stochastic algorithm has the capability to measure the parametric distribution function and validate the predict the reliability rate, mean time to failure and hazard rate. …”
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Semiparametric inference procedure for the accelarated failure time model with interval-censored data by Karimi, Mostafa

“…The main contribution of this research is developing statistical approaches, and introducing new algorithms and resampling methods for analysing interval-censored data through AFT models.…”
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Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

“…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. Each word in the particular document is processed by both algorithms to determine its actual occurrence in the document by which it will first be clustered or grouped into categories based on parts of speech (verb, noun, adjective) which is done by K-Means, then later processed by SVM to determine the actual occurrence of each word in each of the cluster, taking into account whether the words have similar meanings with otherwords in the subsequent cluster. …”
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Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

“…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. Each word in the particular document is processed by both algorithms to determine its actual occurrence in the document by which it will first be clustered or grouped into categories based on parts of speech (verb, noun, adjective) which is done by K-Means, then later processed by SVM to determine the actual occurrence of each word in each of the cluster, taking into account whether the words have similar meanings with otherwords in the subsequent cluster. …”
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Slice sampler algorithm for generalized pareto distribution by Rostami, Mohammad, Adam, Mohd Bakri, Yahya, Mohamed Hisham, Ibrahim, Noor Akma

“…In this paper, we developed the slice sampler algorithm for the generalized Pareto distribution (GPD) model. …”
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Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems by Shakeel Ahmed, Kamboh

“…In order to evaluate the scalability at specific data size the appropriate regression models are fitted through the measured data as functions of number of workers. …”
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Comparison of performance and computational complexity of nonlinear active noise control algorithms by Sahib, Mouayad A., Raja Ahmad, Raja Mohd Kamil

“…The evaluation of the algorithms performance is standardized in terms of the normalized mean square error while the computational complexity is calculated based on the number of multiplications and additions in a single iteration. …”
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Integrated bisect K-means and firefly algorithm for hierarchical text clustering by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

“…However, the Bisect K-means which is a well-known hierarchical clustering algorithm is only able to generate local optimal solutions due to the employment of K-means as part of its process. …”
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Elucidating the effect of process parameters on the production of hydrogen-rich syngas by biomass and coal Co-gasification techniques: A multi-criteria modeling approach by Bahadar A., Kanthasamy R., Sait H.H., Zwawi M., Algarni M., Ayodele B.V., Cheng C.K., Wei L.J.

Tracking The Eyes Using Interdependence Mean Shift Tracking Algorithm With Appropriate Information Provided by Masrullizam, Mat Ibrahim, Syafeeza, Ahmad Radzi, Soraghan, John

“…Most of the developed eyes tracking algorithm are not considered the condition of the eyes that would provide the appropriate information to be used in the processes of the facial analysis algorithm. …”
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Parameter-driven count time series models / Nawwal Ahmad Bukhari by Nawwal , Ahmad Bukhari

“…A key property of our model is that the distributions of the observed count data are independent, conditional on the latent process, although the observations are correlated marginally. …”
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Development Of Double Stage Filter (DSF) On Stereo Matching Algorithm For 3D Computer Vision Applications by Teo, Chee Huat

“…There are two categorized evaluations done on the disparity maps obtained by the algorithms : objective evaluation and subjective evaluation. …”
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