Search Results - parallel using ((stepping algorithm) OR (clustering algorithm))*

Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S., Al-Jumaily A.

“…The results showed that using canopy as a preprocessing step cut the time it proceeds to deal with the significant number of power load abnormalities found in parallel using a fast density peak dataset and the time it proceeds for the k-means algorithm to run. …”

Parallel genetic algorithms for shortest path routing in high- performance computing / Mohd Erman Safawie Che Ibrahim by Che Ibrahim, Mohd Erman Safawie

“…This project focuses on step-up cluster computing and a parallel Genetic Algorithm. …”
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Parallel Processing of Forward-backward Time-stepping Method for Time Domain Inverse Scattering by Kismet, Hong Ping, Moriyama, Toshifumi, Yamaguchi, Yuji, Tanaka, Toshiyuki, Takenaka, Takashi

“…A cluster of 8 PCs is constructed and parallel processing is realized using MPI. …”
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Parallel batch self-organizing map on graphics processing unit using CUDA by Daneshpajouh, H., Delisle, P., Boisson, J.-C., Krajecki, M., Zakaria, N.

“…Although the structure of its training algorithm has a high potential for parallelization, focus of the previous efforts has been on the original Step-wise SOM. …”
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Parallel batch self-organizing map on graphics processing unit using CUDA by Daneshpajouh, H., Delisle, P., Boisson, J.-C., Krajecki, M., Zakaria, N.

“…Although the structure of its training algorithm has a high potential for parallelization, focus of the previous efforts has been on the original Step-wise SOM. …”
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Improving parallel self-organizing map using heterogeneous uniform memory access / Muhammad Firdaus Mustapha by Mustapha, Muhammad Firdaus

“…Self-organizing Map (SOM) is a very popular algorithm that has been used as clustering algorithm and data exploration. …”
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Investigation on the dynamic of computation of semi autonomous evolutionary computation for syntactic optimization of a set of programming codes by Mohammad Sigit Arifianto, Tze, Kenneth Kin Teo, Liau, Chung Fan, Liawas Barukang, Zaturrawiah Ali Omar

“…Secondly, the number of processors in use at each step of the parallel code (degree of parallelism) has an effect on the computation time and the communication time as well. …”
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An efficient parallel clustering algorithm on big data using Spark by Mallik, Moksud Alam, Zulkurnain, Nurul Fariza, Nizamuddin, Mohammed Khaja, Sarkar, Rashel, Ahmed, S K Jamil

“…Here we are proposing a new parallel fuzzy clustering algorithm called "An efficient parallel clustering algorithm on big data using spark" which deals with real-time processing. …”
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Improving parallel Self-organizing Map using heterogeneous uniform memory access / Muhammad Firdaus Mustapha by Mustapha, Muhammad Firdaus

“…Self-organizing Map (SOM) is a very popular algorithm that has been used as clustering algorithm and data exploration. …”
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Parallelization of noise reduction algorithm for seismic data on a beowulf cluster by Aziz, I. A., Sandran, T., Haron, N. S., Hasan, M. H, Mehat, M.

“…The parallel algorithm was developed using C language with the utilization of the Message Passing Interface (MPI) library. …”
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The Parallel Fuzzy C-Median Clustering Algorithm Using Spark for the Big Data by Mallik, Moksud Alam, Zulkurnain, Nurul Fariza, Siddiqui, Sumrana, Sarkar, Rashel

“…Therefore, we develop a Parallel Fuzzy C-Median Clustering Algorithm Using Spark for Big Data that can handle large datasets while maintaining high accuracy and scalability. …”
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Parallel algorithms on some numerical techniques using PVM platform on a cluster of workstations by Alias, Norma, Mohamed, Mohd. Salleh Sahimi, Abdullah, Abdul Rahman

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Parallel matrix-multiplication algorithm on network of workstations by Md. Aminuddin, Rusdi, Abdullah, Rosni, Hassan, Suhaidi

“…We present the comparison in terms of speed between serial algorithm and the parallel algorithm when we run them on our cluster. …”
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K Nearest Neighbor Joins And Mapreduce Process Enforcement For The Cluster Of Data Sets In Bigdata by Md Shah, Wahidah, Othman, Mohd Fairuz Iskandar, Hussian Hassan, Ali Abdul, Talib, Mohammed Saad, Mohammed, Ali Abdul Jabbar

“…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 block methods for solving higher order ordinary differential equations directly by Omar, Zurni

“…A new parallel algorithm for solving systems of ODEs using variable step size and order is also developed. …”
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A genetic-based HAC technique for parallel clustering of bilingual Malay-English corpora by Ng Zhen Wei, Chan Chen Jie, Rayner Alfred, Joe Henry Obit

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Parallel Processing of RSAAlgorithm Using MPI Library by Wan Dagang, Wan Rahaya

“…This report explains the project of developing Parallel Processing of RSA Algorithm Using MPI Library. …”
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Development of a parallel clustering of bilingual corpora based on reduced terms by Leow, Ching Leong

“…The quality of clustering bilingual text documents is highly influenced by the quality of the bag-of-word presentation of Malay text articles presented to the clustering algorithm. …”
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Parallel execution of distributed SVM using MPI (CoDLib) by Salleh N.S.M., Suliman A., Ahmad A.R.

“…Instead of using a single machine for parallel computing, multiple machines in a cluster are used. …”

The AGEB algorithm for solving the heat equation in two space dimensions and its parallelization on a distributed memory machine by Alias N., Sahimi M.S., Abdullah A.R.