• East Asian mathematical journal
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• v.37 no.3
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• pp.333-354
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• 2021

A support vector machine (SVM) is a state-of-the-art machine learning model rooted in structural risk minimization. SVM is underestimated with regards to its application to real world problems because of the difficulties associated with its use. We aim at showing that the performance of SVM highly depends on which kernel function to use. To achieve these, after providing a summary of support vector machines and kernel function, we constructed experiments with various benchmark datasets to compare the performance of various kernel functions. For evaluating the performance of SVM, the F1-score and its Standard Deviation with 10-cross validation was used. Furthermore, we used taylor diagrams to reveal the difference between kernels. Finally, we provided Python codes for all our experiments to enable re-implementation of the experiments.

• Journal of Korea Technology Innovation Society
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• v.14 no.4
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• pp.965-982
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• 2011

Currently, dependency of natural and energy resources on world economy may not be more serious than any before increasing the uncertainty of Korea's national economy, especially as China uses unexpectedly fast glowing portion of world resources. Due to insufficient natural resources and unmatured renewable energy system, it is very important for Korea to secure the energy sources not only for national prosperity but also security for the future. In this regard, importance and necessity of nuclear energy as a major electric power source in Korea are in need to be emphasized. Korea currently imports all the necessary enriched uranium for fabrication of nuclear fuel from abroad. Thus, it is extremely important to establish a secured supply system for enriched uranium regardless of the global political unstability as well as economic fluctuation. In order to build the nuclear fuel procurement system, it is required to analyze the global market status, current enrichment service systems, and the future technology under development. For this purpose, this study comparatively analyzes the laser based advanced technology for uranium enrichment under development in the United States, which is assumed to be 2~3 times more economically viable than currently available technologies.