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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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New Quarter-Sweep-Based Accelerated Over-Relaxation Iterative Algorithms and their Parallel Implementations in Solving the 2D Poisson Equation
Published 2010“…Newly developed parallel AOR QS and AOR MEG methods for distributed mem-ory parallel machine are shown to be eficient for large sparse matrices, which occur in large sizes of problem. …”
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Data discovery algorithm for scientific data grid environment
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Finite element model for crack propagation using master-workers method
Published 2004“…This paper describes an algorithm for parallel assembling of the stiffness matrix in simulation of crack propagation in distributed memory environment using masterworkers method. …”
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An efficient cache replacement algorithm for minimizing the error rate in L2-STT-MRAM caches
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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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Classification for large number of variables with two imbalanced groups
Published 2020“…This study proposed two algorithms of classification namely Algorithm 1 and Algorithm 2 which combine resampling, variable extraction, and classification procedure. …”
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Communication and computation rate-cheating problems in divisible load scheduling: revisited
Published 2015“…The traditional divisible load scheduling assumes that the processors report their true computation and communication rates. In the real applications, the processors may cheat the algorithm which means that the processors might not report their true computation or communication rates. …”
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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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A modified artificial neural network (ANN) algorithm to control shunt active power filter (SAPF) for current harmonics reduction
Published 2013“…The novelty control design is an artificial neural network (ANN) adopting a modified mathematical algorithm (a modified delta rule weight-updating W-H) and a suitable alpha value (learning rate value) which determines the filters optimal operation. …”
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Optimal timber transportation planning in tropical hill forest using bees algorithm
Published 2022“…The model uses grid cell-sized 10 m x 10 m characterised with timber locations, volume and fixed and variable costs to represent the study area. …”
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Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms
Published 2024“…The classification algorithm used in this research is the Convolutional Neural Network (CNN) algorithm. …”
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Optimized clustering with modified K-means algorithm
Published 2021“…Clustering technique is able to find hidden patterns and to extract useful information from huge data. Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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Coronary artery stenosis detection and visualization / Tang Sze Ling
Published 2015“…The performance evaluation results show that the stenosis detection algorithm performs better average sensitivity than several state-of-the-art algorithms.…”
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Multi-criteria divisible load scheduling in binary tree network
Published 2016“…The traditional divisible load scheduling assumes that the processors report their true computation and communication rates, i.e., they do not cheat the algorithm. In the real applications, the processors may cheat the algorithm, which means, the processors might not report their true computation or communication rates. …”
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Dengue outbreak prediction: hybrid meta-heuristic model
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