Search Results - (( time distribution function algorithm ) OR ( data distribution function algorithm ))*
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1
Reliability Analysis and Prediction of Time to Failure Distribution of an Automobile Crankshaft
Published 2015“…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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2
Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems
Published 2014“…To implement the parallel algorithms a distributed parallel computing laboratory using easily available low cost computers is setup. …”
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3
A new Gompertz-three-parameter-lindley distribution for modeling survival time data
Published 2025“…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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Parameter-driven count time series models / Nawwal Ahmad Bukhari
Published 2018“…In this study, a parameter-driven count time series model with three different distributions that are Poisson, zero-inflated Poisson and negative binomial was developed. …”
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5
Semiparametric inference procedure for the accelarated failure time model with interval-censored data
Published 2019“…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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6
Sizing and placement of solar photovoltaic plants by using time-series historical weather data
Published 2018“…By adopting a time-varying commercial load, the proposed algorithm was applied on IEEE 33 bus and IEEE 69 bus distribution networks. …”
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7
Sizing and placement of solar photovoltaic plants by using time-series historical weather data
Published 2018“…By adopting a time-varying commercial load, the proposed algorithm was applied on IEEE 33 bus and IEEE 69 bus distribution networks. …”
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8
Optimal network reconfiguration and intelligent service restoration prediction technique based on Cuckoo search spring algorithm / Mohamad Izwan Zainal
Published 2022“…In addition, objective function using the same CSSA algorithm were applied i.e., Vmin and Ploss as the objective function, and multi-objective involves Vmin and Ploss as the objective function. …”
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9
Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah
Published 2015“…Empirical cumulative distribution function (CDF) model is presented in evaluating the real traffic distribution. …”
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Some families of count distributions for modelling zero-inflation and dispersion / Low Yeh Ching
Published 2016“…A popular distribution for the modelling of discrete count data is the Poisson distribution. …”
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11
Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah
Published 2015“…Empirical cumulative distribution function (CDF) model is presented in evaluating the real traffic distribution. …”
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12
Sizing and Placement of Battery-Sourced Solar Photovoltaic (B-SSPV) Plants in Distribution Networks
Published 2021“…The proposed algorithm is applied on IEEE 33 bus and IEEE 69 bus test distribution networks and optimum results are acquired for different time varying voltage dependent load models. …”
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Network reconfiguration and control for loss reduction using genetic algorithm
Published 2010“…Tests have shown that the differences are demonstrated only in execution time to arrive the best fitness function of the Genetic Algorithm. …”
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14
Improvement on optimal coordination of directional overcurrent relays in mesh distribution network system using artificial intelligence technique
Published 2015“…This research work propose the artificial intelligent (AI) solution on the conventional objective function (COF) and the modified objective function (MOF) formulation, with the application of genetic algorithm (GA) optimization solver, to determine each relay best optimal operation parameters selection for the time dial settings (TDS), plug setting (PS) and response time to fault accordingly. …”
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15
Parametric and Semiparametric Competing Risks Models for Statistical Process Control with Reliability Analysis
Published 2004“…Plots of survival distribution function against failure time are used to examine the predicted survival patterns for the two types of failures. …”
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16
A study on regional GDP forecasting analysis based on radial basis function neural network with genetic algorithm (RBFNN-GA) for Shandong economy
Published 2022“…The center of radial basis function neural network and smoothing factor to take a uniform distribution of the random radial basis function artificial neural network will be the focus of this study. …”
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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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Enhanced Q-Learning algorithm for potential actions selection in automated graphical user interface testing
Published 2023“…Furthermore, the proposed techniques based on the QLearning algorithm do not consider context-based actions. Thus, these techniques are unable to detect failures that occur due to the improper use of context data, which is becoming an increasingly common issue in mobile applications nowadays. …”
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19
Forecasting FTSE Bursa Malaysia KLCI Trend with Hybrid Particle Swarm Optimization and Support Vector Machine Technique
Published 2013“…The SVM algorithm uses the Radial Basis Function (RBF) kernel function and optim ization of the gam ma and large margin parameters are done using the PSO algorithm. …”
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Examination invigilation timetable using Genetic Algorithm / Mohamad Fakhrullah Ibrahim
Published 2025“…The current manual process is labor-intensive, error-prone, and time-consuming. To overcome these issues, a system utilizing a Genetic Algorithm (GA) was developed to automate and optimize the timetabling process. …”
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