Search Results - (( probable distribution using algorithm ) OR ( parameter simulation based algorithm ))

Fair bandwidth distribution marking and scheduling algorithm in network traffic classification by Al-Kharasani, Ameen Mohammed Abdulkarem

“…This is achieved by using a new design algorithm by separating marker TCP and UDP protocols and extended the marking probability for injecting more green and yellow traffic into the network. …”
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Confidence intervals (CI) for concentration parameter in von Mises distribution and analysis of missing values for circular data / Siti Fatimah binti Hassan by Hassan, Siti Fatimah

“…The second part of the study is on the confidence intervals (CI) for the concentration parameter in von Mises distribution. Several methods in constructing the CI for the concentration parameter are proposed including CI based on circular population, CI based on the asymptotic distribution of ˆ , CI based on the distribution of 휃 and 푅 and also CI based on bootstrap-t method. …”
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Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari by Satari, Siti Zanariah

“…We first look at the concentration parameter of von Mises distribution. The von Mises distribution is the most commonly used probability distribution of a circular random variable, and the concentration of a circular data set is measured using the mean resultant length. …”
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Statistical performance of agglomerative hierarchical clustering technique via pairing of correlation-based distances and linkage methods by Nurshaziana, Mohamad Shamsuri

“…To validate the clustering model on real data, the Spearman-average algorithm was applied to cluster Juru river basin data based on five water quality parameters. …”
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Cash-flow analysis of a wind turbine operator by Muhamad Razali N.M., Hashim A.H.

“…Two-parameter Weibull type probability density function (PDF) is used to model wind profile at two locations. …”

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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Fuzzy-based multi-agent approach for reliability assessment and improvement of power system protection by Nadheer Abdulridha, Shalash

“…In addition, another two agents have been developed based on Monte Carlo simulation. The first agent employed fuzzy parameters such as, current with its means and variances and the second agent is the probability of outage capacity for each state. …”
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A memory-guided Jaya algorithm to solve multi-objective optimal power flow integrating renewable energy sources by Ahmadipour M., Ali Z., Ramachandaramurthy V.K., Ridha H.M.

“…To ensure fair comparisons, parameter configurations for all algorithms are automated using the parameter tuning tool iterated racing (irace). …”

Development of a multi criteria decision support system using convolutional neural network and jaya algorithm for water resources management / Chong Kai Lun by Chong , Kai Lun

“…Besides, a Bayesian uncertainty analysis was carried out to quantify the model output behaviors due to derivation from the uncertainty in the input parameters. A Bayesian method for CNN using TensorFlow Probability was used in this study. …”
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Determining penetration limit of central distributed generation topology in radial distribution networks by Suliman, Mohamed Saad Abdelgadir

“…The beta probability density functions were used to model the photovoltaic generation, while the normal probability density functions were used to model the load demand. …”
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Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani by Ehsan Taslimi , Renani

“…To evaluate the performance of the Weibull parameters’ estimator methods, two sets of data are considered, one based on simulated data with different random variable size and the other based on actual data collected from a wind farm in Iran. …”
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Modelling and Forecasting the Kuala Lumpur Composite Index Rate of Returns Using Generalised Autoregressive Conditional Heteroscedasticity Models by Abdul Muthalib, Maiyastri

“…Methods for correcting the outliers and splitting the heterogeneous data are proposed. The EM algorithm is applied to split the heterogeneous data, and the estimated parameters are used to correct the outlying data using the Mahalanobis Distance. …”
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A simulation based fly optimisation algorithm for swarms of mini autonomous surface vehicles application by Zainal Abidin, Zulkifli

“…The optimal simulation parameters can be used for the real application. …”
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Novel distributed algorithm for coalition formation for enhanced spectrum sensing in cognitive radio networks by Tahir, Mohammad, Habaebi, Mohamed Hadi, Islam, Md Rafiqul

“…The coalitions formed using the algorithm are stable and do not deviate from the final matching. …”
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Optimization of turning parameters using genetic algorithm method by Shah Izwandi, Mohd Zawawi

“…The simulation based on Genetic Algorithm are successful develop and the optimum parameters values are obtained from the simulation.…”
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PSAT : a pairwise test data generation tool based on simulated annealing algorithm by Goh, Ghee Hau

“…This research is about the research on developing a Pairwise Test Data Generation Tool based on Simulated Annealing (SA) algorithm which named as PSAT. …”
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Novel distributed algorithm for coalition formation in cognitive radio networks for throughput enhancement using matching theory by Tahir, Mohammad, Habaebi, Mohamed Hadi, Islam, Md Rafiqul

“…The coalitions formed using the algorithm are stable and do not deviate from the final matching. …”
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An empirical study of density and distribution functions for ant swarm optimized rough reducts by Pratiwi, Lustiana, Choo, Yun Huoy, Draman @ Muda, Azah Kamilah

“…Coexistence, cooperation, and individual contribution to food searching by a particle (ant) as a swarm (colony) survival behavior, depict the common characteristics of both PSO and ACO algorithms. Ant colony approach in Ant Swarm algorithm generates local solutions which satisfy the Gaussian distribution for global optimization using PSO algorithm. …”
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Optimization of milling parameters using ant colony optimization by Mohd Saupi, Mohd Sauki

“…The simulation based on ACO algorithm are successful develop and the optimization of parameters values is to maximize the production rate is obtain from the simulation.…”
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The Implementation of a Machine Learning-based Routing Algorithm in a Lab-Scale Testbed by Ridwan M.A., Radzi N.A.M., Azmi K.H.M., Ahmad A., Abdullah F., Ahmad W.S.H.M.W.

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