Search Results - (( weibull distributions using algorithm ) OR ( parameter optimization sensor algorithm ))
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Estimation Of Weibull Parameters Using Simulated Annealing As Applied In Financial Data
Published 2023“…The finding reveals that the Weibull distribution is well-suited to describing the investment behaviour of the MPS based on the estimates via the SA algorithm. …”
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Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah
Published 2015“…Four traffic distribution which are normal, lognormal, Weibull and exponential distribution are fitted and derived. …”
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Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah
Published 2015“…Four traffic distribution which are normal, lognormal, Weibull and exponential distribution are fitted and derived. …”
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4
Competing risks for reliability analysis using Cox’s model
Published 2007“…Purpose – Cox’s model with Weibull distribution and Cox’s with exponential distribution are the most important models in reliability analysis. …”
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Bayesian survival and hazard estimates for Weibull regression with censored data using modified Jeffreys prior
Published 2013“…For the Weibull model with right censoring and unknown shape, the full conditional distribution for the scale and shape parameters are obtained via Gibbs sampling and Metropolis-Hastings algorithm from which the survival function and hazard function are estimated. …”
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Variational Bayesian inference for exponentiated Weibull right censored survival data
Published 2023“…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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Multi-mobile agent itinerary planning algorithms for data gathering in wireless sensor networks: a review paper
Published 2017“…The review shows that most of the algorithms used one parameter to find the optimal number of mobile agents in multi-agent itinerary planning without utilizing other parameters. …”
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Peak time bandwidth control algorithms with fitted traffic model on broadband network YouTube video traffic: article / Aini Azmi
Published 2016“…Results presents traffic characterizations are identified based on two (2) parameters Cumulative Distribution Functions (CDF) traffic model. Maximum Likelihood Estimator (MLE) technique is used to fit the best distribution model. …”
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Peak time bandwidth control algorithms with fitted traffic model on broadband network YouTube video traffic / Aini Azmi
Published 2016“…Results presents traffic characterizations are identified based on two (2) parameters Cumulative Distribution Functions (CDF) traffic model. Maximum Likelihood Estimator (MLE) technique is used to fit the best distribution model. …”
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Parameter adaptation for ant colony system in wireless sensor network
Published 2019“…The Ant Colony System (ACS) algorithm has been applied in solving packet routing problems in Wireless Sensor Networks (WSNs). …”
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Probabilistic evaluation of wind power generation
Published 2023“…The paper presents an algorithm developed for a random wind speed generator governed by the probability density function of Weibull distribution and evaluates the WTG's output by using the power curve of wind turbines. …”
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An Optimized ANN Measure-Correlate-Predict Method for Long-term Wind Prediction in Malaysia
Published 2023Conference Paper -
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Statistical modeling of the electromechanical behaviour of BI-2223 composite wires
Published 2024text::Final Year Project -
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Whale optimization algorithm based on tent chaotic map for feature selection in soft sensors
Published 2025“…One of the powerful optimization algorithms that is used for feature selection is the Whale Optimization Algorithm (WOA), which is a nature-inspired metaheuristic optimization algorithm that mimics the social behavior of humpback whales. …”
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Delay and energy-aware routing for efficient data collection in wireless sensor networks / Ihsan Ali
Published 2024“…The IDBA-AFW evaluates the fitness of relay nodes based on multiple criteria, such as energy efficiency, throughput, and end-to-end delay. Both Bat Algorithm parameters and AFW parameters are adaptively tuned to balance exploration and exploitation throughout the optimization process. …”
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Multiobjective optimization using particle swarm optimization with non-Gaussian random generators
Published 2016“…The stochastic engines operate using the Weibull distribution, Gamma distribution, Gaussian distribution and a chaotic mechanism. …”
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Multiobjective optimization using particle swarm optimization with non-Gaussian random generators
Published 2016“…The stochastic engines operate using the Weibull distribution, Gamma distribution, Gaussian distribution and a chaotic mechanism. …”
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Multiobjective optimization using particle swarm optimization with non-Gaussian random generators
Published 2016“…The stochastic engines operate using the Weibull distribution, Gamma distribution, Gaussian distribution and a chaotic mechanism. …”
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Multiobjective optimization using particle swarm optimization with non-Gaussian random generators
Published 2016“…The stochastic engines operate using the Weibull distribution, Gamma distribution, Gaussian distribution and a chaotic mechanism. …”
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