Search Results - (( property distribution computer algorithm ) OR ( data distribution computer algorithm ))
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Optimal search algorithm in a big database using interpolation–extrapolation method
Published 2019“…Search using traditional binary-search algorithm can be accelerated by employing an interpolation search technique when the data is regularly distributed. …”
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Improved genetic algorithm for scheduling divisible data grid application
Published 2007“…Data Grid technology promises geographically distributed scientists to access and share physically distributed resources such as computing resources, networks, storages, and most importantly data collections for large scale data intensive problems. …”
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Estimation Of Weibull Parameters Using Simulated Annealing As Applied In Financial Data
Published 2023“…The present study proposes a simulated annealing algorithm (SA) in estimating the parameters of Weibull distribution with application to modified internal rate of return data (MIRR).The objective is to examine the investment potential of the shari’ah compliance companies of the Malaysia property sector (MPS). …”
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Semiparametric inference procedure for the accelarated failure time model with interval-censored data
Published 2019“…A computationally simple two-step iterative algorithm, called estimationapproximation algorithm, is introduced for estimating the parameters of the model on the basis of the rank estimators. …”
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A cluster-based hybrid replica control protocol for high availability in data grid
Published 2019“…In recent years, the number of distributed nodes has become very large in Grid computing system. …”
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Simulated annealing algorithm for scheduling divisible load in large scale data grids
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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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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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Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…One of the main issues in genetic k-means based algorithms is their sensitivity to outliers and unevenly distributed clusters due to the mean compromised computations. …”
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Thesis -
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Load-Balancing Models for Scheduling Divisible Load on Large Scale Data Grids
Published 2009“…In many data grid applications, data can be decomposed into multiple independent sub datasets and distributed for parallel execution. …”
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Entropy in portfolio optimization / Yasaman Izadparast Shirazi
Published 2017“…It has been established that though variance is computationally simple and very popular among practitioners, a more flexible measure of risk is demanded to cope with the uncertainty in real data that are typically non-normally distributed. …”
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Modifying maximum likelihood test for solving singularity and outlier problems in high dimensional cases
Published 2021“…To improve the ML estimators and to maintain the high breakdown point while having high dimensional data sets, a new robust estimator of banded Cholesky and L₁-median with Weiszfeld algorithm, MLѡвсн was suggested. …”
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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“…The study analyzes data from 62 publicly listed Malaysian property businesses spanning the period from 2008 to 2019. …”
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Flexible content authorization using digital rights management in cloud computing / Ali Hussain
Published 2021“…This study also represents Macaroons as an alternative method for temper proof and flexible sharing of data over distributed computing. The study demonstrates that the proposed method can provide the immutable data integrity protection with flexible policy definition to limit the access. …”
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Geometric feature descriptor and dissimilarity-based registration of remotely sensed imagery
Published 2024journal::journal article -
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Predicting the popularity of tweets using the theory of point processes.
Published 2019“…The intensity process of the model is interpretable as a cluster Poisson process, which implies that the model can be simulated using the cascading algorithm similar to that used for the efficient simulation of Hawkes processes, and the prediction can be done properly by exploiting the probabilistic properties of the model. …”
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UMK Etheses -
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