Ç¥ÁØÈ­ Âü¿©¾È³»

TTAÀÇ Ç¥ÁØÇöȲ

Ȩ > Ç¥ÁØÈ­ °³¿ä > TTAÀÇ Ç¥ÁØÇöȲ

Ç¥ÁعøÈ£ TTAK.KO-10.1297 ±¸Ç¥ÁعøÈ£
Á¦°³Á¤ÀÏ 2021-12-08 ÃÑÆäÀÌÁö 15
ÇѱÛÇ¥Áظí ÀüÀÚÄÚ¿¡¼­ °úµµ»óÅ¿¡¼­ÀÇ °¡½ººÐ·ù¸¦ À§ÇÑ ¼øȯ½Å°æ¸Á Àû¿ë ÂüÁ¶¸ðµ¨
¿µ¹®Ç¥Áظí Reference Model of Recurrent Neural Network for Gas Classification from Transient State at Electronic Nose
Çѱ۳»¿ë¿ä¾à ÀÌ Ç¥ÁØÀº °¡½º ¼¾¼­ ¾î·¹À̸¦ »ç¿ëÇÏ´Â ÀüÀÚÄÚ ½Ã½ºÅÛ¿¡¼­ µö·¯´× ¾Ë°í¸®ÁòÀÇ ÀÏÁ¾ÀÎ ¼øȯ½Å°æ¸Á(Recurrent Neural Network)À» ÀÌ¿ëÇÏ¿© °úµµ»óÅ¿¡¼­ °¡½º¸¦ ÀνÄÇÏ°í ºÐ·ùÇϱâ À§ÇØ ÇÊ¿äÇÑ µ¥ÀÌÅÍ Ãëµæ ¹æ¹ý, µ¥ÀÌÅÍÀÇ ±¸Á¶¿Í ±¸¼º ¹æ¹ý, µ¥ÀÌÅÍ¿Í ¼øȯ½Å°æ¸Á °úÀÇ ÀÎÅÍÆäÀ̽º ¹æ¹ý µîÀ» Á¤ÀÇÇÑ´Ù.
¿µ¹®³»¿ë¿ä¾à The standard is a data acquisition method required to recognize and classify gases in transients using a recurrent neural network, a kind of deep learning algorithm in an electronic nose system using a gas sensor array, and the structure and composition of the data. It defines methods, methods of interfacing data with recurrent neural networks
±¹Á¦Ç¥ÁØ
°ü·ÃÆÄÀÏ TTAK.KO-10.1297.pdf TTAK.KO-10.1297.pdf            

ÀÌÀü
»çÀ̹ö-¹°¸® ½Ã½ºÅÛ(CPS)ÀÇ ¾ÈÀü¡¤½Å·Ú¼º È®º¸ Áöħ - Á¦5ºÎ: CPS ¾ÈÀü¡¤½Å·Ú¼º ÇÁ·ÎÇÊ ÁÖµµ Å×½ºÆà ÇÁ·¹ÀÓ¿öÅ©
´ÙÀ½
Àü±âÂ÷ µ¥ÀÌÅÍ Ç÷§Æû - Á¦2ºÎ: µ¥ÀÌÅÍ ±¸¼º¿ä¼Ò ¹× Çü½Ä