Search Results - (( normal distribution modified algorithm ) OR ( parallel distribution selection algorithm ))
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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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Distributed generation with parallel connected inverter
Published 2009“…This paper presents the design and analysis of a new configuration of parallel connected inverter suitable for Distributed Generation Application. …”
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Modeling The Modified Internal Rate Of Return (Mirr) For Long-Term Investment Strategy By The Assumption Of Gamma Distribution
Published 2023“…It offers greater flexibility compared to the commonly used normal distribution.…”
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Soap performance enhancement for high volume messaging / Ali Baba Dauda
Published 2018“…Two messages formats, normal and compressed (modified algorithm) with the size ranging 1MB - 22 MB were generated and executed 50 times in both web services. …”
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Modifying maximum likelihood test for solving singularity and outlier problems in high dimensional cases
Published 2021“…On the other hand, several shortcomings such as inconsistency under normal distribution, based on small sample size with large variables in high dimensions were discovered. …”
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Dynamic robust bootstrap method based on LTS estimators
Published 2009“…In order to make reliable inferences about the parameters of a model, require that the parameter estimates are normally distributed. Nevertheless, in real situations, many estimates are not normal and the use of bootstrap method is more appropriate as it does not rely on the normality assumption. …”
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Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares
Published 2009“…One of the important assumptions of the linear model is that the error terms are normally distributed. Unfortunately, many researchers are not aware that the performance of the OLS can be very poor when the data set that one often makes a normal assumption, has a heavy-tailed distribution which may arise as a result of the presence of outliers. …”
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Regenerative braking strategy for electric vehicles using improved adaptive genetic algorithm
Published 2017“…One uses Standard Genetic Algorithm (SGA), the second strategy uses Improved Adaptive Genetic Algorithm (IAGA). …”
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Efficiency of 4253HT smoothers in extracting signal from noise and their applications in forecasting
Published 2019“…This is asserted by the smooth value which was close to the signal, indicating its capability to extract signal from highly fluctuating noise. The modified 4253HT using adaptive mean showed the most effective, compared to others, in extracting low, moderate and high frequency of sinusoidal signal from the noise with 10%, 25%, 50% and 75% contaminated normal distribution. …”
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Extreme air pollutant data analysis using classical and Bayesian approaches
Published 2015“…MTM algorithm is an extension of MH algorithm, designed to improve the convergence of MH algorithm by performing parallel computation. …”
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Robust Kernel Density Function Estimation
Published 2010“…To do this evaluation, the mixtures of bivariate normal distribution with different percentage of contribution are simulated. …”
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An enhanced cluster head selection algorithm for routing in mobile AD-HOC network
Published 2017“…The performance of ECRP algorithms was compared with other cluster based algorithms. …”
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Pemetaan Pm10 Dan Aot Menggunakan Teknik Penderiaan Jauh Di Semenanjung Malaysia
Published 2006“…The developed algorithms are two-band algorithm, terma linear and modified algorithm from the combination of the visible and infrared thermal bands. …”
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…Here, the memory consumption can be reduced by enabling a feature selection algorithm that excludes nonrelevant features and preserves the relevant ones. the algorithm is developed based on the variable length of the PSO. …”
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Random sampling method of large-scale graph data classification
Published 2024“…After that, we randomly select a subset of data blocks, each being a random sample of the graph dataset, and compute the different graph property distributions. …”
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Multi-objective portfolio selection with skewness preference: An application to the stock and electricity markets / Karoon Suksonghong
Published 2014“…However, MV efficient portfolios may not yield superior result due to the fact that the distribution of returns to financial assets is not normal but skewed. …”
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Nonlinear three-dimensional finite elements for composite concrete beams
Published 2012“…Therefore in this study, new interface elements have been developed,while modified constitutive law have been applied and new computational algorithm is utilised. …”
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