Search Results - (( parallel distribution means algorithm ) OR ( parallel evaluation path algorithm ))
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Quantitative and qualitative analysis of unmanned aerial vehicle's path planning using master-slave parallel vector-evaluated genetic algorithm
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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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An evaluation of parallel genetic algorithm for solving shortest path routing problem
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Implementation of Parallel K-Means Algorithm to Estimate Adhesion Failure in Warm Mix Asphalt
Published 2020“…The results showed that the PKIP algorithm decreases the execution time up to 30 to 46 if compared with the sequential k means algorithm when implemented using multiprocessing and distributed computing. …”
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Minimizing machining airtime motion with an ant colony algorithm
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A test case generation framework based on UML statechart diagram
Published 2018“…Current studies also hardly address loops and parallel paths issues, and achieved low coverage criteria. …”
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Autonomous anomaly detection using density-based features in streaming data / Muhammmad Yunus Iqbal Basheer
Published 2023“…It is because the parallel mechanism is able to handle high-speed streaming data. …”
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A hybrid rate control mechanism for forwarding and congestion control in named data network
Published 2020“…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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Dengue outbreak prediction: hybrid meta-heuristic model
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Optimization of Workload Allocation Problem in a Network of Heterogeneous Computer Systems
Published 2005“…A new algorithm of workload allocation scheme using First Come First Serve discipline in conjunction with optimization of GE queueing systems is proposed for minimizing mean queue length and mean response time in a network of computer systems. …”
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Extreme air pollutant data analysis using classical and Bayesian approaches
Published 2015“…MTM algorithm is an extension of MH algorithm, designed to improve the convergence of MH algorithm by performing parallel computation. …”
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Investigation of QAM based on mean square error (MSE) channel estimation (CE) for MIMO-OFDM pilot based system / Mohd Ariff Ibrahim
Published 2013“…The Least Square Error (LSE) and Discrete Fourier Transform (DFT) BER are not shown because these are other CE techniques and Mean Square Error (MSE) is used just by applying the algorithm from Least Square Error (LSE) and converted into MSE with combination of few complex matrix correlations.…”
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Generic DNA encoding design scheme to solve combinatorial problems
Published 2015“…The complexity of combinatorial problems is classified as NP meaning that algorithms are yet to exist to efficiently solve the problem. …”
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Communication and computation rate-cheating problems in divisible load scheduling: revisited
Published 2015“…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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An adaptive controller of hydro generators for smart grid application in Malaysia
Published 2010“…The controller has been modeled considering the existing Malaysia' distribution network of mini hydro power plant connected in parallel to the grid. …”
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3d Morphing And Shape Transformation Using Slices
Published 2009“…Most of the existing shape transformation algorithms involve a lot of user intervention, do not scale well when the number of input objects is more than two and are not scalable in parallel and distributed computing environment whenever needed. …”
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…Here, the memory consumption can be reduced by enabling a feature selection algorithm that excludes nonrelevant features and preserves the relevant ones. the algorithm is developed based on the variable length of the PSO. …”
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