Search Results - (( evolution optimization bat algorithm ) OR ( parallel visualization matching algorithm ))
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Multi-Swarm bat algorithm
Published 2023“…In this study a new Bat Algorithm (BA) based on multi-swarm technique called the Multi-Swarm Bat Algorithm (MSBA) is proposed to address the problem of premature convergence phenomenon. …”
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Parallel batch self-organizing map on graphics processing unit using CUDA
Published 2018“…The most computationally expensive parts of its training algorithm (such as steps to compute distance between each data vector and neuron, and determining the Best Matching Unit based on minimum distance) are identified and mapped on GPU to be processed in parallel. …”
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Parallel batch self-organizing map on graphics processing unit using CUDA
Published 2018“…The most computationally expensive parts of its training algorithm (such as steps to compute distance between each data vector and neuron, and determining the Best Matching Unit based on minimum distance) are identified and mapped on GPU to be processed in parallel. …”
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Quality of service and energy efficient aware (QEEA) scheduling algorithm for long term evolution (LTE) network / Nurulanis Mohd Yusoff
Published 2017“…Basically, the QEEA is based on the Time Domain (TD) and Frequency Domain (FD) scheduling where it is dependent on the QoS requirements to allocate resources. The proposed algorithm is compared against other scheduling algorithms, namely, the Channel and QoS Aware (CQA), Priority Set Scheduler (PSS), Proportional Fair (PF), Maximum Throughput (MT) and Blind Average Throughput (BAT). …”
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Adopting morphology method in camera based EAN-13 1D barcode recognition using Simulink: article / Siti Nor Safinaz Ozaimidi
Published 2012“…A result of barcode numbers saved in file.mat is used for product matching code. The percentage of success is 94.44% and failure of the system is 5.56%.…”
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Adopting morphology method in camera based EAN-13 1D barcode recognition using Simulink / Siti Nor Safinaz Ozaimidi
Published 2012“…A result of barcode numbers saved in file.mat is used for product matching code. The percentage of success is 94.44% and failure of the system is 5.56%.…”
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Thesis
