Search Results - (( parallel distribution factor algorithm ) OR ( property distribution function algorithm ))
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Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm
Published 2025“…Parallel power loads anomalies are processed by a fast-density peak clustering technique that capitalizes on the hybrid strengths of Canopy and K-means algorithms all within Apache Mahout's distributed machine-learning environment. …”
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Investigation on the dynamic of computation of semi autonomous evolutionary computation for syntactic optimization of a set of programming codes
Published 2007“…Genetic Algorithm as one of the Evolutionary Computation method improve the execution of parallel programming codes by optimizing the number of processors and the distribution of data. …”
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3
Improved black-winged kite algorithm and finite element analysis for robot parallel gripper design
Published 2024“…The Good Point Set (GPS), nonlinear convergence factor, and adaptive t-distribution method improve BKA, which enhances exploration and exploitation performance, convergence speed, and solution quality. …”
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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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5
Design and analysis of management platform based on financial big data
Published 2023“…In addition, a financial data management platform based on distributed Hadoop architecture is designed, which combines MapReduce framework with the fuzzy clustering algorithm and the local outlier factor (LOF) algorithm, and uses MapReduce to operate in parallel with the two algorithms, thus improving the performance of the algorithm and the accuracy of the algorithm, and helping to improve the operational efficiency of enterprise financial data processing. …”
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Parameter-driven count time series models / Nawwal Ahmad Bukhari
Published 2018“…The first part of the study derives the explicit solutions of the moment properties (mean, variance, skewness and kurtosis) of the distributions together with their respective autocovariance and autocorrelation functions, up to the ith order. …”
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7
On a new transmuted three-parameter lindley distribution and its applications
Published 2024“…The statistical properties of the TTHPLD model, which are based on moments, order statistics, hazard rate functions, reliability functions, and Renyi entropy, have been studied. …”
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Semiparametric inference procedure for the accelarated failure time model with interval-censored data
Published 2019“…Also, a one-step iterative algorithm, called expected rank algorithm, is introduced which is more complicated than the estimation-approximation algorithm, but more accurate. …”
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9
Some families of count distributions for modelling zero-inflation and dispersion / Low Yeh Ching
Published 2016“…Some of the theoretical properties of the distributions are derived and the distributions' characteristics are studied. …”
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10
A Novel Approach Of Groebner Bases Computation For Safety Analysis Of Distributed Discrete Controllers
Published 2019“…One of the favorite topic is the formal verification via model checking, which is to verify whether a mathematical model of a system meets the formal specification that describes the property to be checked. In this research, our main objective is to generate a new model checking computation method based on Groebner bases algorithm for safety property analysis of distributed discrete controllers. …”
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11
Modeling The Modified Internal Rate Of Return (Mirr) For Long-Term Investment Strategy By The Assumption Of Gamma Distribution
Published 2023“…However, simultaneously estimating all three parameters (shape, scale, and growth) through the maximum-likelihood function is computationally complex. Alternative approaches such as the Simulated Annealing (SA) algorithm, which maximizes the log-likelihood function, and Bayesian MCMC estimation are considered. …”
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12
Conjunctions in biological neural architectures for visual pose estimation / Tom´As Maul
Published 2006“…A highly parallel approach based on simple inter-map conjunctions, or correspondence distributions, is chosen and tested on synthetic and real patterns. …”
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
Published 2016“…In addition, the classifier is also optimized such that it has a good generalization property. The main keys of the new classifier are based on the new kernel method, new learning metric and a new optimization algorithm in order to optimize the SVM decision function. …”
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15
An improved bat algorithm with artificial neural networks for classification problems
Published 2016“…Then, the proposed BAGD algorithm is frnther hybridized with Simulated Annealing (SA) and Genetic Algorithm (GA) to perform two stage optimization in which the former algorithm finds the optimal solution and the latter algorithm starts from where the first one is converged. …”
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A New Cryptosystem Based on Decimal Numbers and Nonlinear Function
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17
High performance visualization of human tumor growth software
Published 2008“…The platform for high performance computing of the parallel algorithms run on a distributed parallel computer system. …”
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Enhanced Automated Framework For Cattle Tracking And Classification
Published 2022“…Mean-shift strength is its sensitivity to object’s movement and colour distribution by using similarity function but, with inability to track object’s non-linear movement and full occlusion as its weakness.…”
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High performance simulation for brain tumors growth using parabolic equation on heterogeneous parallel computer systems
Published 2007“…This paper focuses on the implementation of parallel algorithm for the simulation of brain tumours growth using one dimensional parabolic equation, design on a distributed parallel computer system. …”
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Automated-tuned hyper-parameter deep neural network by using arithmetic optimization algorithm for Lorenz chaotic system
Published 2023“…AOA makes use of the distribution properties of mathematics’ primary arithmetic operators, including multiplication, division, addition, and subtraction. …”
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