KCC 2021
Current Result Document : 668 / 668
ÇѱÛÁ¦¸ñ(Korean Title) |
½Ã°è¿ µ¥ÀÌÅÍ¿¡ ´ëÇÑ »õ·Î¿î Ư¡ ÃßÃâ ¾Ë°í¸®Áò Á¦½Ã ¹× ±ºÁýÈ ¼º´É ºÐ¼® : RP-CNN Autoencoder°ú Wavelet, Autoencoder ºñ±³ |
¿µ¹®Á¦¸ñ(English Title) |
Suggesting A New Feature Extraction Algorithm for Time Series Data and Comparing Clustering Performance : RP-CNN Autoencoder vs. Wavelet vs. Autoencoder |
ÀúÀÚ(Author) |
ÀÌ¿øºó
±è¹ü¼®
¸ð»óÀÏ
½É´ÙÇý
ÃÖ¿µ±Ù
Wonbin Lee
Beom Seok Kim
Sang-il Mo
Dahye Shim
Yeongkeun Choi
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¿ø¹®¼ö·Ïó(Citation) |
VOL 48 NO. 01 PP. 1831 ~ 1833 (2021. 06) |
Çѱ۳»¿ë (Korean Abstract) |
½Ã°è¿ µ¥ÀÌÅÍ ±ºÁýÈ¿¡ ÀÖ¾î ½Ã°è¿ µ¥ÀÌÅÍÀÇ Æ¯Â¡À» ÃßÃâÇÏ´Â °úÁ¤Àº ÇʼöÀûÀÌ´Ù. ±ºÁýÈ¿¡ Àû¿ëµÇ´Â ½Ã°è¿ µ¥ÀÌÅÍÀÇ ¿ë·® ¹× Â÷¿øÀº ´ëºÎºÐ Å©°í ÀÌ´Â Â÷¿øÀÇ ÀúÁÖ(Curse of Dimensionality)¸¦ ÀÏÀ¸Å°¹Ç·Î ¼º´É ÀúÇÏÀÇ ÁÖ¿øÀÎÀ¸·Î ÀÛ¿ëÇÑ´Ù. ÀÌ¿¡ ´ëÇÑ ÇØ°áÃ¥À¸·Î Â÷¿ø Ãà¼Ò°¡ Á¦½ÃµÇÁö¸¸ °úÇÑ Â÷¿ø Ãà¼Ò ±â¹ýÀ¸·Î µ¥ÀÌÅÍ Æ¯Â¡À» ÃßÃâÇϸé Á¤º¸ ¼Õ½Ç·Î ÀÎÇØ ±ºÁýÈ ¼º´ÉÀÌ ¿ÀÈ÷·Á ÀúÇ쵃 ¼ö ÀÖ´Ù. º» ³í¹®Àº ±âÁ¸¿¡ »ç¿ëµÈ Ư¡ ÃßÃâ ¹æ¹ýÀÎ, Wavelet º¯È¯ ¹× Autoencoder ¿Ü¿¡, ¶óµð¿À ½ÅÈ£ ŽÁö¿¡ Àû¿ëµÈ RP-CNNÀ» ÀϺΠº¯ÇüÇÏ¿© '½Ã°è¿ µ¥ÀÌÅÍÀÇ À̹ÌÁöȸ¦ ÅëÇÑ Æ¯Â¡ ÃßÃâ' ±â¹ýÀÎ RP-CNN AutoencoderÀ» Á¦½ÃÇÏ¿´°í À̸¦ ÅëÇØ ÃßÃâÇÑ Æ¯Â¡ º¤Å͸¦ K-Means ¾Ë°í¸®Áò¿¡ Àû¿ëÇÏ¿© ±ºÁýÈ ¼º´ÉÀ» ºñ±³ÇÑ´Ù. ±× °á°ú, ÀûÀº Â÷¿øÀ¸·Î °¥¼ö·Ï RP-CNN Autoencoder°¡ ³ôÀº ±ºÁýÈ ¼º´ÉÀ» º¸ÀÌ´Â °ÍÀ» È®ÀÎÇÏ¿´°í, RP-CNN Autoencoder´Â ±ºÁýÈ¿¡¼ À¯ÀǹÌÇÑ Æ¯Â¡ ÃßÃâ º¤Å͸¦ »ý¼ºÇÒ ¼ö ÀÖÀ½À» ¾Ë ¼ö ÀÖ´Ù. |
¿µ¹®³»¿ë (English Abstract) |
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Å°¿öµå(Keyword) |
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