Abstract
This paper proposes genetic-based k-nearest neighbor method for chaff echo identification. Weather radar provides various data: location, velocity, direction, and range of typhoon or precipitation, precipitation intensity, altitude and location of thunderstorm and rainfall. Above this data, topography echo, anomalous echo, second echo and chaff echo are observed from weather radar, and they are disrupt weather forecasting. They are called non-weather echo. In order to improve weather forecasting, we propose genetic-basedk-nearest neighbor for chaff echo identification. Experimental result shows that chaff echoes are well removed, so performance weather forecasting will also be improved.
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Kim, J., Han, H., Yu, J., Lee, H., Kim, S. (2013). Genetic-Based k-Nearest Neighbor for Chaff Echo Detection. In: Lee, J., Lee, M.C., Liu, H., Ryu, JH. (eds) Intelligent Robotics and Applications. ICIRA 2013. Lecture Notes in Computer Science(), vol 8103. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40849-6_37
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DOI: https://doi.org/10.1007/978-3-642-40849-6_37
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-40848-9
Online ISBN: 978-3-642-40849-6
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