¶óÆæÆ®¦¢Ä«Æä¦¢ºí·Î±×¦¢´õº¸±â
¾ÆÄ«µ¥¹Ì Ȩ ¸í»çƯ°­ ´ëÇבּ¸½Ç޹æ Á¶°æ½Ç¹« µ¿¿µ»ó°­ÀÇ Çѱ¹ÀÇ ÀüÅëÁ¤¿ø ÇÐȸº° ³í¹®
ÇÐȸº° ³í¹®

Çѱ¹°Ç¼³°ü¸®ÇÐȸ
Çѱ¹°ÇÃà½Ã°øÇÐȸ
Çѱ¹µµ·ÎÇÐȸ
Çѱ¹»ý¹°È¯°æÁ¶ÀýÇÐȸ
Çѱ¹»ýÅÂÇÐȸ
Çѱ¹¼öÀÚ¿øÇÐȸ
Çѱ¹½Ä¹°ÇÐȸ
Çѱ¹½Ç³»µðÀÚÀÎÇÐȸ
Çѱ¹ÀÚ¿ø½Ä¹°ÇÐȸ
Çѱ¹ÀܵðÇÐȸ
Çѱ¹Á¶°æÇÐȸ
Çѱ¹Áö¹Ý°øÇÐȸ
Çѱ¹ÇÏõȣ¼öÇÐȸ
Çѱ¹È¯°æ»ý¹°ÇÐȸ
Çѱ¹È¯°æ»ýÅÂÇÐȸ

Çѱ¹¼öÀÚ¿øÇÐȸ / v.29, no.4, 1996³â, pp.109-118
ãêÌèØÑìµÖå¿¡ ÀÇÇÑ Ë½éëçãö´¿¡ °üÇÑ æÚϼ
( A Study on Rainfall Prediction by Neural Network )
¿À³²¼±;¼±¿ìÁßÈ£; ¸ñÆ÷ÇØ¾ç´ëÇб³ ÇØ¾ç ¹× Á¶¼±°øÇкÎ;¼­¿ï´ëÇб³ ÃÑÀå;
 
ÃÊ ·Ï
½Å°æ¸ÁÀÌ·ÐÀº ºÐ»ê±â¾ï¼ºÁú°ú º´·Ä±¹¼Ò󸮸¦ ¼öÇàÇÏ´Â ³úÀÇ È°µ¿À» ÀÌ·ÐÈ­ÇÑ ¼öÇиðÇüÀÌ´Ù. ÀÌ·¯ÇÑ ½Å°æ¸ÁÀÌ·ÐÀÇ ÀåÁ¡Àº ºÐ·ù¹®Á¦, ´ë±Ô¸ð·Î °áÇÕµÈ ÃÖÀûÈ­¹®Á¦, ºñ¼±Çü »ç»ó¹®Á¦ µî¿¡¼­ Àß ³ªÅ¸³ª¹Ç·Î, ÀÌ Á¡À» ÀÌ¿ëÇÏ¿© º¹ÀâÇÑ °­¿ìÀÇ ¿¹ÃøÀ» ½ÃµµÇÏ¿´´Ù. ½Å°æ¸ÁÀÌ·ÐÀ» Àû¿ëÇϱâ À§Çؼ­ ¿¬¼ÓÀûÀÎ °ªÀ¸·Î Ç¥½ÃµÇ´Â ÀÔ·ÂÀÚ·á¿Í Ãâ·ÂÀڷḦ ÇнÀÇÑ ÈÄ °­¿ì¿¹ÃøÀ» ½ÃÇàÇÒ ¼ö ÀÖ´Â ´ÙÃþ½Å°æ¸Á ¸ðÇüÀ» ±¸¼ºÇÏ¿´´Ù. ½Å°æ¸ÁÀ̷п¡ ÀÇÇÑ °­¿ì¿¹ÃøÀº ¼­¿ïÁö¿ª°ú ¼Ò¾ç°­À¯¿ªÀÇ 1 ½Ã°£ ´ëÀ§ °­¿ìÀÚ·á¿¡ Àû¿ëÇÏ¿´´Ù. ±× °á°ú´Â ´ëü·Î ¸¸Á·ÇÒ ¸¸ÇÏ¿´´Ù. µû¶ó¼­ ½Å°æ¸ÁÀÌ·ÐÀº ¾çÁúÀÇ ÀÚ·á°¡ ÃæºÐÈ÷ È®º¸µÉ °æ¿ìº¹ÀâÇÑ °­¿ìÇö»óÀ» Àß ¿¹ÃøÇÒ °ÍÀ¸·Î ±â´ëµÈ´Ù.
The neural network is a mathematical model of theorized brain activity which attempts to exploit the parallel local processing and distributed storage properties. The neural metwork is a good model to be applied for the classification problem, large combinatorial optimization and nonlinear mapping. A multi-layer neural network is constructed to predict rainfall. The network learns continuourvalued input and output data. Application of neural network to 1-hour real data in Seoul metropolitan area and the Soyang River basin shows slightly good predictions. Therefore, when good data is available, the neural network is expected to predict the complicated rainfall successfully.
 
Ű¿öµå
 
Çѱ¹¼öÀÚ¿øÇÐȸÁö / v.29, no.4, 1996³â, pp.109-118
Çѱ¹¼öÀÚ¿øÇÐȸ
ISSN : 1738-9488
UCI : G100:I100-KOI(KISTI1.1003/JNL.JAKO199611920097512)
¾ð¾î : Çѱ¹¾î
³í¹® Á¦°ø : KISTI Çѱ¹°úÇбâ¼úÁ¤º¸¿¬±¸¿ø
¸ñ·Ïº¸±â
ȸ»ç¼Ò°³ ±¤°í¾È³» ÀÌ¿ë¾à°ü °³ÀÎÁ¤º¸Ãë±Þ¹æÄ§ Ã¥ÀÓÀÇ ÇѰè¿Í ¹ýÀû°íÁö À̸ÞÀÏÁÖ¼Ò ¹«´Ü¼öÁý °ÅºÎ °í°´¼¾ÅÍ
   

ÇÏÀ§¹è³ÊÀ̵¿