Search Results - (( parallel distribution mining algorithm ) OR ( parallel evaluation path algorithm ))

Quantitative and qualitative analysis of unmanned aerial vehicle's path planning using master-slave parallel vector-evaluated genetic algorithm

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Master-Slave Parallel Vector-Evaluated Genetic Algorithm for Path Planning of Unmanned Aerial Vehicles by Pierre, Djamalladine Mahamat

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Parallel execution of distributed SVM using MPI (CoDLib) by Salleh N.S.M., Suliman A., Ahmad A.R.

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

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An evaluation of parallel genetic algorithm for solving shortest path routing problem by Rina Azlin Razali

Minimizing machining airtime motion with an ant colony algorithm by Abdullah, Haslina, Ramli, Rizauddin, Abd Wahab, Dzuraidah, Abu Qudeiri, Jaber

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A test case generation framework based on UML statechart diagram by Salman, Yasir Dawood

“…Current studies also hardly address loops and parallel paths issues, and achieved low coverage criteria. …”
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Random sampling method of large-scale graph data classification by Rashed Mustafa, Mohammad Sultan Mahmud, Mahir Shadid

“…Mining a large number of graphs becomes a challenging task because state-of-the-art methods are not scalable due to the memory limit. …”
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A hybrid rate control mechanism for forwarding and congestion control in named data network by Alsamman, Mohammed Gamal

“…Named Data Networking (NDN) is an emerging Internet architecture that employs a pull-based, in-path caching, hop-by-hop, and multi-path transport architecture. …”
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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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Online teleoperation of writing manipulator through graphics processing unit based accelerated stereo vision by Abu Raid, Fadi Imad Osman

“…These algorithms are then parallelized using Compute Unified Device Architecture CUDA C language to run on Graphics Processing Unit GPU for hardware acceleration. …”
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DC-based PV-powered home energy system by Sabry, Ahmad H.

“…A controller based on an algorithm of one time maximum power point (MPP) is proposed to mitigate those losses. …”
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