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Image Segmentation With Cyclic Load Balanced Parallel Fuzzy C - Means.
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Performance Comparison of Parallel Bees Algorithm on Rosenbrock Function
Published 2012“…The other downside of the Bee Algorithm is that it has needless computation. This means that it spends a long time for the bees algorithm converge the optimum solution. …”
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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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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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Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform
Published 2009“…By the means of higher performance computing, the computation cannot be relying on just one single set of cluster. …”
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One-dimensional finite element discretization of crack propagation through parallel computation
Published 2010“…We have implemented one dimensional finite element discretization to solve crack propagation problem. The parallel algorithm with parallel computer system has been used in order to perform the computational analysis of finite element for this study. …”
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Peningkatan halaju suapan maksimum penginterpolasi CNC dedenyut rujukan menggunakan pengaturcaraan selari
Published 2011“…This situation is also required in interpolator algorithm. The existing interpolator is not using parallel programming which every task have not been execute simultaneous in concurrent manner although using multi-cores processor computer, thus, the more time is needed for the iteration time especially for a complex and large scale of process. …”
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An efficient indexing and retrieval of iris biometrics data using hybrid transform and firefly based K-means algorithm title
Published 2019“…The enhanced method combines three transformation methods for analyzing the iris image and extracting its local features. It uses a weighted K-means clustering algorithm based on the improved FA to optimize the initial clustering centers of K-means algorithm, known as Weighted K-means clustering-Improved Firefly Algorithm (WKIFA). …”
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Generic DNA encoding design scheme to solve combinatorial problems
Published 2015“…However, DNA computing can solve the problem in linear time since the parallel processing power of DNA computing is able to generate a solution in a single process. …”
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Autonomous anomaly detection using density-based features in streaming data / Muhammmad Yunus Iqbal Basheer
Published 2023“…Consequently, to handle these data, computer algorithms must adapt to their characteristics. …”
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Communication and computation rate-cheating problems in divisible load scheduling: revisited
Published 2015“…The traditional divisible load scheduling assumes that the processors report their true computation and communication rates. 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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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“…Other service distributional models such as exponential, Erlang-k and Gamma have also been used to expand the work applicability. 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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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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