Search Results - parallel solution ((using algorithm) OR (clustering algorithm))*
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Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm
Published 2025“…After classifying the time set using the canopy with the K-means algorithm and the vector representation weighted by factors, the clustering impact is assessed using purity, precision, recall, and F value. …”
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A spark-based parallel fuzzy C median algorithm for web log big data
Published 2022“…Based on the Rand Index and SSE (sum of squared error), the parallel Fuzzy C median algorithm's performance is evaluated in the PySpark platform. …”
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Parallel Processing of Forward-backward Time-stepping Method for Time Domain Inverse Scattering
Published 2008“…A cluster of 8 PCs is constructed and parallel processing is realized using MPI. …”
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Improving parallel self-organizing map using heterogeneous uniform memory access / Muhammad Firdaus Mustapha
Published 2018“…Self-organizing Map (SOM) is a very popular algorithm that has been used as clustering algorithm and data exploration. …”
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Single and Multiple variables control using Tree Physiology Optimization
Published 2017“…This paper presents the tuning of single-input single-output (SISO), and multiple-input multiple-output (MIMO) control system using Tree Physiology Optimization (TPO). TPO is a metaheuristic optimization algorithm that has a clustered diversification search strategy inspired from plant shoots growth. …”
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Quantification and segmentation of breast cancer diagnosis: efficient hardware accelerator approach
Published 2022“…In addition, a new image clustering algorithm anticipates the need for largescale serial and parallel processing. …”
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Application of parallel ensemble Monte Carlo technique in charge dynamics simulation
Published 2008“…The use of Parallel Virtual Machine (PVM) standards when running the parallel algorithm of the ensemble MC simulation been proposed Some results of the development are also presented in this paper.…”
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…Therefore, we propose a prominent approach that integrates each of the NN, a meta-heuristic based on an evolutionary genetic algorithm (GA), and a core online-offline clustering (Core). …”
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Application of parallel ensemble Monte Carlo technique in charge dynamics simulation
Published 2008“…We have proposed the use of Parallel Virtual Machine (PVM) standards when running the parallel algorithm of the ensemble MC simulation. …”
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Solving traveling salesman problem on cluster compute nodes
Published 2009“…The sequential algorithm is then converted into a parallel algorithm by integrating it with the Message Passing Interface (MPI) libraries so that it can be executed on a cluster computer. …”
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Parallel metaheuristic algorithm for route planning using CUDA
Published 2025“…This research will be focusing on developing a Parallel Metaheuristic Algorithm for Route Planning using CUDA to improve the efficiency and performance of route planning. …”
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Final Year Project / Dissertation / Thesis -
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K Nearest Neighbor Joins And Mapreduce Process Enforcement For The Cluster Of Data Sets In Bigdata
Published 2018“…K Nearest Neighbor Joins (KNN join) are regarded as highly primitive and expensive operations in the data mining.The efficient use of KNN join has proven good results in finding the objects from two data sets prevailed in the huge databases.This has been achieved with the combination of K-Nearest Neighbor query and join operation to find the distinct objects from different data sets.MapReduce is a newly introduced program with the combination of Map Procedure method and Reduce Method widely used in BigData.MapReduce is enriched with parallel distributed algorithm to find the results on a cluster of data sets in BigData.In this paper,the combination of KNN join and MapReduce methods are utilized on the cluster of data sets in BigData for knowledge discovery.Exploring the pinpoint data from huge data sets stored in Big Data demands the distributed large scale data processing.The present research paper is focusing on generic steps for KNN joins exploration operations on MapReduce.The operations of KNN Join are targeted to perform the data partitioning and data pre-processing and necessary calculations.By utilizing the combination of KNN joins with MapReduce methods on BigData data sets will demonstrate a solution for complex computational analysis. …”
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Parallel Homologous Search With Hirschberg Algorithm: A Hybrid MPI-Pthreads Solution.
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Fast Finite Difference Time Domain Algorithms for Solving Antenna Application Problem
Published 2008“…Results show that these new sequential and parallel algorithms run faster than the standard sequential and parallel FDTD algorithms. …”
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Parallel block methods for solving higher order ordinary differential equations directly
Published 1999“…A new parallel algorithm for solving systems of ODEs using variable step size and order is also developed. …”
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Sequential and parallel multiple tabu search algorithm for multiobjective urban transit scheduling problems
Published 2018“…Additionally, the MTS algorithm is also implemented in parallel computing to produce parallel MTS for generating comparable solutions in shorter computational times. …”
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Parallel block backward differentiation formulas for solving ordinary differential equations.
Published 2008“…Numerical results are given to compare the speedup and efficiency of parallel algorithm and that of sequential algorithm.…”
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Efficient Sequential and Parallel Routing Algorithms in Optical Multistage Interconnection Network
Published 2005“…This routing problem is an NPhard problem. Many algorithms are designed by many researchers to perform this routing such as window method, sequential algorithm, degree-descending algorithm, simulated annealing algorithm, genetic algorithm and ant colony algorithm.This thesis explores two approaches, sequential and parallel approaches. …”
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Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures
Published 2020“…Meta-heuristic algorithms have widely used in HPAs due to their global optimization ability. …”
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