Search Results - (( a distribution a algorithm ) OR ( parameter estimation ((acs algorithm) OR (bayes algorithm)) ))
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Parameter estimation of Kumaraswamy Burr type X models based on cure models with or without covariates
Published 2017“…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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Predicting the popularity of tweets using the theory of point processes.
Published 2019“…The knowledge is combined using a novel empirical Bayes type approach, where the prior distribution for the model parameter is constructed based on the external knowledge, and the likelihood is calculated based on the internal knowledge. …”
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Fault-current predetermination using time- limited CT secondary side measurements by the covariance-Prony method
Published 2004“…Samples of the CT secondary current are collected until the onset of saturation, and are operated upon using a covariance-Prony algorithm to estimate the aforementioned critical parameters. …”
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Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines
Published 2020“…The prior result from the Matlab model of the adaptive numerical distance relay connected on midpoint integrated STATCOM power grid system indeed establish the existence of the under-reach effect for the relay zone-3 elements ing far-end short circuit fault at the coverage boundary leading to wrong impedance estimation. The BayesNet provides the best integrated MLADR fault classifier model better at a 5 % significance level than other deployed algorithms in the intelligent supervised learning model realization. …”
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Indirect Rotor Field Oriented Control of Induction Motor With Rotor Time Constant Estimation
Published 2004“…Since the position of the rotor flux vector is estimated in an IRFOC scheme, and is dependent on the motor model (more specifically the rotor parameters), these parameters must be obtained accurately and match the motor parameters at all times. …”
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Sensor-less vector control using adaptive observer scheme for controlling the performance of the induction motor / Mazhar Hussain Abbasi
Published 2013“…Internal parameters are used, for example, feed-forward compensator of current controller and parameters of observer model in sensor less position. …”
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Analysing the performance of classification algorithms on diseases datasets
Published 2023“…The proposed classification algorithms measure the diseases using the disease datasets which estimates the accurate prediction. …”
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Optimized scheduling for an airconditioning system based on indoor thermal comfort using the multiobjective improved global particle swarm optimization
Published 2018“…The main contribution of this paper is a new optimized AC scheduling approach that focuses on indoor thermal comfort using a new multi-objective optimization algorithm, called the improved global particle swarm optimization (IGPSO), which able to find better optimal solutions faster than its original version, the global particle swarm optimization (GPSO) algorithm. …”
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Interpolation and extrapolation techniques based Neural Network in estimating the missing ionospheric TEC data
Published 2024Conference Paper -
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Evaluation of reference signal estimation techniques for the control of shunt active power filter
Published 2023Conference paper -
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Predictive analytic dashboard for desalter and crude distillation unit
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Distributive and self-sustainable scheduling algorithm for wireless sensor networks
Published 2013“…In this paper, we propose a distributive and self-sustainable scheduling algorithm (DSSA). …”
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Distributive and self-sustainable scheduling algorithm for wireless sensor networks
Published 2013“…In this paper, we propose a distributive and self-sustainable scheduling algorithm (DSSA). …”
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Distributive and self-sustainable scheduling algorithm for wireless sensor networks
Published 2013“…In this paper, we propose a distributive and self-sustainable scheduling algorithm (DSSA). …”
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Automated surveillance in distributed, visual networks: an empirical comparison of recent algorithms
Published 2014“…The selected algorithms were then applied in a distributed fashion at each node. …”
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