Search Results - (( weibull distribution process algorithm ) OR ( parallel distribution factor algorithm ))

Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah by Abdullah, Mohd Azrul

“…Analysis results present Weibull Distribution model is the best fitted model. …”
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Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah by Abdullah, Mohd Azrul

“…Analysis results present Weibull Distribution model is the best fitted model. …”
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Peak time bandwidth control algorithms with fitted traffic model on broadband network YouTube video traffic: article / Aini Azmi by Azmi, Aini

“…Bandwidth Control Algorithms is developed based on Peak Time of day and night. …”
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Peak time bandwidth control algorithms with fitted traffic model on broadband network YouTube video traffic / Aini Azmi by Azmi, Aini

“…Bandwidth Control Algorithms is developed based on Peak Time of day and night. …”
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Risk analysis of the copula dependent aggregate discounted claims with Weibull inter-arrival time by Siti Norafidah Mohd Ramli, Sharifah Farah Syed Yusoff Alhabshi, Nur Atikah Mohamed Rozali

“…We model the recursive moments of aggregate discounted claims, assuming the inter-claim arrival time follows a Weibull distribution to accommodate overdispersed and underdispersed data set. …”
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Parametric and Semiparametric Competing Risks Models for Statistical Process Control with Reliability Analysis by Mohamed Elfaki, Faiz Ahmed

“…From the simulation study for this particular case, we can conclude that Weibull distribution describes well the nature of the model concerned as compared to the exponential distribution in terms of the mean value of parameter estimates, bias, and the root means square error. …”
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Statistical modeling of the electromechanical behaviour of BI-2223 composite wires by Muhammad Faris Fuaad

Multiobjective optimization using particle swarm optimization with non-Gaussian random generators by Ganesan, T., Vasant, P., Elamvazuthi, I.

“…The two non-Gaussian distributions are the Weibull and Gamma distributions. …”
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Multiobjective optimization using particle swarm optimization with non-Gaussian random generators by Ganesan, T., Vasant, P., Elamvazuthi, I.

“…The two non-Gaussian distributions are the Weibull and Gamma distributions. …”
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Multiobjective optimization using particle swarm optimization with non-Gaussian random generators by Ganesan, T., Vasant, P., Elamvazuthi, I.

“…The two non-Gaussian distributions are the Weibull and Gamma distributions. …”
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Multiobjective optimization using particle swarm optimization with non-Gaussian random generators by Ganesan, T., Vasant, P., Elamvazuthi, I.

“…The two non-Gaussian distributions are the Weibull and Gamma distributions. …”
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Adaptive policing and shaping algorithms on inbound traffic using generalized Pareto distribution / Nor Azura Ayop by Ayop, Nor Azura

“…Log likelihood estimation technique is used to fit the best 2-parameter CDF compared to Weibull, Normal and Rician distribution model. The percentage level 5% under original bandwidth used is developed on policing and shaping algorithms to control bandwidth used. …”
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Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S., Al-Jumaily A.

“…Parallel power loads anomalies are processed by a fast-density peak clustering technique that capitalizes on the hybrid strengths of Canopy and K-means algorithms all within Apache Mahout's distributed machine-learning environment. …”

Investigation on the dynamic of computation of semi autonomous evolutionary computation for syntactic optimization of a set of programming codes by Mohammad Sigit Arifianto, Tze, Kenneth Kin Teo, Liau, Chung Fan, Liawas Barukang, Zaturrawiah Ali Omar

“…Genetic Algorithm as one of the Evolutionary Computation method improve the execution of parallel programming codes by optimizing the number of processors and the distribution of data. …”
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Improved black-winged kite algorithm and finite element analysis for robot parallel gripper design by Haohao, Ma, As’arry, Azizan, Yanwei, Feng, Lulu, Cheng, Delgoshaei, Aidin, Ismail, Mohd Idris Shah, Ramli, Hafiz Rashidi

“…The Good Point Set (GPS), nonlinear convergence factor, and adaptive t-distribution method improve BKA, which enhances exploration and exploitation performance, convergence speed, and solution quality. …”
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Some families of count distributions for modelling zero-inflation and dispersion / Low Yeh Ching by Low, Yeh Ching

“…Two new mixed Poisson distributions, namely a three-parameter Poisson-exponentiated Weibull distribution and a fourparameter generalized Sichel distribution is introduced to model over dispersed, zeroinflated and long-tailed count data. …”
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Design and analysis of management platform based on financial big data by Chen, Yuhua, Mustafa, Hasri, Zhang, Xuandong, Liu, Jing

“…In addition, a financial data management platform based on distributed Hadoop architecture is designed, which combines MapReduce framework with the fuzzy clustering algorithm and the local outlier factor (LOF) algorithm, and uses MapReduce to operate in parallel with the two algorithms, thus improving the performance of the algorithm and the accuracy of the algorithm, and helping to improve the operational efficiency of enterprise financial data processing. …”
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Conjunctions in biological neural architectures for visual pose estimation / Tom´As Maul by Tom´As, Maul

“…A highly parallel approach based on simple inter-map conjunctions, or correspondence distributions, is chosen and tested on synthetic and real patterns. …”
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Artificial neural network algorithm for predicting the surface roughness in end milling of Inconel 718 alloy by Hossain, Mohammad Ishtiyaq, Amin, A. K. M. Nurul, Patwari, Muhammed Anayet Ullah

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Development of warranty management visualisation for automotive aftermarket with integration of AI by Abdul Hamid, Abdul Hamid, Adull Manan, Nor Fazli, Ismail, Mohd Fauzi, Abdul Wahab, Abdul Malek, Khalit, Muhammad Ilham

“…Advanced analytics techniques including Weibull distribution modelling for failure prediction and Python based anomaly detection algorithms were implemented to identify high risk components and unusual claim behaviours. …”
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