Search Results - (( parallel estimation path algorithm ) OR ( parallel estimation machine algorithm ))
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Magnetic resonance imaging sense reconstruction system using FPGA / Muhammad Faisal Siddiqui
Published 2016“…Parallel imaging is a robust method for accelerating the data acquisition in Magnetic Resonance Imaging (MRI). …”
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Early detection of breast cancer using wave elliptic equation with high performance computing
Published 2008“…The mathematical model of Helmholtz’s model is used to visualize the growth of breast cancer. Parallel Virtual Machine (PVM) is emphasized as communication platform in parallel computer system. …”
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A new method for decreasing cell-load variation in dynamic cellular manufacturing systems
Published 2016“…In this article, a new method is proposed for scheduling dynamic cellular manufacturing systems in the presence of bottleneck and parallel machines. The aim of this method is to control cell load variation during the process of determining the best trading off values between in-house manufacturing and outsourcing. …”
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A multi-period scheduling of dynamic cellular manufacturing systems in the presence of cost uncertainty
Published 2016“…It can cause long queues in front of machines and impose extra costs to the cellular layouts. …”
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Short-term Gini coefficient estimation using nonlinear autoregressive multilayer perceptron model
Published 2024“…System Identification (SI), a methodology utilized in domains like engineering and mathematical modeling to construct or refine dynamic system models from captured data, relies significantly on the Nonlinear Auto-Regressive (NAR) model due to its reliability and capability of integrating nonlinear functions, complemented by contemporary machine learning strategies and computational algorithms to approximate complex system dynamics to address these limitations. …”
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Improving energy consumption in cloud computing datacenters using a combination of energy-aware resource allocation and scheduling mechanism
Published 2017“…Nowadays, DNA plays a vital role in many computing applications due to the massive processing parallelism. In addition, using fuzzy theory in genetic algorithm reduces the iteration of producing the population and assigning the suitable resources to the tasks-based and task length in the node capacity. …”
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