Search Results - parallel computing ((window algorithm) OR (mining 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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Line clipping based on parallelism approach and midpoint intersection
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Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems
Published 2014“…To implement the parallel algorithms a distributed parallel computing laboratory using easily available low cost computers is setup. …”
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Efficient hardware design for palm-dorsa vein image enhancement
Published 2018“…For hardware design of thinning, parallel pipelined with Concurrent Condition Check Unit hardware architecture has been developed to enable the parallelism of the thinning algorithm. …”
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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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The Parallel Fuzzy C-Median Clustering Algorithm Using Spark for the Big Data
Published 2024“…Apache Spark is one of the most widely used large-scale data processing engines due to its speed, low latency in-memory computing, and powerful analytics. 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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A novel association rule mining approach using TID intermediate itemset
Published 2018“…Designing an efficient association rule mining (ARM) algorithm for multilevel knowledge-based transactional databases that is appropriate for real-world deployments is of paramount concern. …”
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Measuring GPU-accelerated parallel SVM performance using large datasets for multi-class machine learning problem
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Optimizing OLAP heterogeneous computing based on Rabin-Karp algorithm
Published 2013“…Keywords— OLAP, heterogeneous computing, Rabin-Karp, data mining, pattern recognition.…”
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A novel association rule mining approach using TID intermediate itemset
Published 2018“…Designing an efficient association rule mining (ARM) algorithm for multilevel knowledge-based transactional databases that is appropriate for real-world deployments is of paramount concern. …”
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…This research opens a wide range of future work to be considered, which includes applying the proposed method in other areas such as web mining, text mining or multimedia mining; and extending the proposed approach to work in parallel computing in data mining.…”
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Resource Minimization in a Real-time Depth-map Processing System on FPGA
Published 2011“…Depth-map algorithm allows camera system to estimate depth. It is a computational intensive algorithm, but can be implemented with high speed on hardware due to the parallelism property. …”
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MINIMIZATION OF RESOURCE UTILIZATION FOR A REAL-TIME DEPTH-MAP COMPUTATIONAL MODULE ON FPGA
Published 2011“…The algorithm is computationally intensive and therefore more effective to be implemented on hardware such as the Field Programmable Gate Array (FPGA). …”
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Hybrid metaheuristics for QOS-aware service composition / Hadi Naghavipour
Published 2022“…On that basis, the second contribution of this thesis is proposing a fast fuzzy evolutionary algorithm with minimal stochastic behaviour. Furthermore, this thesis contributes to the body of knowledge by introducing a novel method called Fuzzy Rough set Genetic Algorithm (FRGA) that take on efficiency of metaheuristics while reducing search space by leveraging the data mining aspect of rough set theory. …”
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Random sampling method of large-scale graph data classification
Published 2024“…Since the data blocks in this model are much smaller than the entire data set, it is more efficient to analyze them on a standalone small machine, and multiple data blocks can be analyzed on multiple nodes of the cluster in parallel. Finally, we classified the graphs of data blocks using the SVM algorithm. …”
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Online teleoperation of writing manipulator through graphics processing unit based accelerated stereo vision
Published 2021“…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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