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Current Result Document :
ÇѱÛÁ¦¸ñ(Korean Title) |
µö·¯´× ±â¹Ý ¹«¿ª ¼öÃâ °¡°Ý ¿¹Ãø ¸ðµ¨ |
¿µ¹®Á¦¸ñ(English Title) |
Predicting the Future Price of Export Items in Trade Using a Deep Regression Model |
ÀúÀÚ(Author) |
±èÁöÈÆ
ÀÌÁöÇ×
Kim Ji Hun
Lee Jee Hang
|
¿ø¹®¼ö·Ïó(Citation) |
VOL 11 NO. 10 PP. 0427 ~ 0436 (2022. 10) |
Çѱ۳»¿ë (Korean Abstract) |
»ê¾÷Åë»óÀÚ¿øºÎ¿¡¼ Á¦°øÇÏ´Â KOTRA ¹«¿ª µ¥ÀÌÅÍ´Â ÇØ´ç Ç°¸ñ°ú ÇØ´ç ±¹°¡¿¡ ´ëÇÏ¿© GDP, °ü¼¼À², ºñÁî´Ï½º Á¡¼ö, °ú/Â÷³âµµ ¼öÃâ±Ý¾× µîÀ» Á¦°øÇÑ´Ù. ±×·¯³ª ¹«¿ª ¼öÃâÇ°¸ñÀº ¼ö¾øÀÌ ¸¹À»»Ó´õ·¯ ±×¿¡ µû¸¥ ´ë·®ÀÇ µ¥ÀÌÅ͸¦ ¸Å³â ¼öÀÛ¾÷ ±â¹Ý ºÐ¼®À» ÅëÇØ À¯ÀǹÌÇÑ °á°ú¸¦ À̲ø¾î³»´Â °ÍÀº »ó´çÈ÷ Å« ½Ã°£°ú ºñ¿ëÀ» ¿ä±¸ÇÑ´Ù. µû¶ó¼ À̹ø ¿¬±¸¿¡¼± ´ë·®ÀÇ µ¥ÀÌÅ͸¦ ÇнÀÇÏ¿© ´Ü±â°£¿¡ Àúºñ¿ëÀ¸·Î °á°ú ¿¹ÃøÀÌ °¡´ÉÇÑ ´ÙÃþ ÆÛ¼ÁÆ®·Ð ¸ðµ¨À» ±¸ÇöÇÏ°í ¼º´ÉÀ» Æò°¡ÇÏ¿´´Ù. ¸ÕÀú µö·¯´× ±â¹Ý ¹«¿ª ¼öÃâ °¡°Ý ¿¹Ãø ¸ðµ¨À» ÀϹÝÀû ´Ùº¯·® ȸ±Í ¸ðµ¨°ú ºñ±³ÇÏ¿´À» ¶§, ¿¹Ãø ¿À·ù¿Í ÇнÀ ½Ã°£ Ãø¸é¿¡¼ Åë°èÀûÀ¸·Î ¿ì¼öÇÑ ¼º´ÉÀ» º¸¿´´Ù. ¼öÃâ °¡°Ý µ¥ÀÌÅÍ´Â ½Ã°è¿ ¼Ó¼ºÀÌ ÀÖÀ» °ÍÀ¸·Î ¿¹»óÇÏ´Â ¹Ù, Àº´Ð ³ëµåµéÀÌ ¸ðµÎ ¿¬°áµÈ ´ÙÃþ ÆÛ¼ÁÆ®·Ð°ú ¼øȯ ½Å°æ¸ÁÀ» ÀÌ¿ëÇÏ¿© ¼öÃâ °¡°Ý µ¥ÀÌÅ͸¦ ¿¹ÃøÇÏ¿´´Ù. ±× °á°ú »õ·Î¿î µ¥ÀÌÅÍ¿¡ ´ëÇØ ¼öÃâ °¡°Ý ¿¹ÃøÀ» À§ÇÑ ÀϹÝÈ ´É·ÂÀº ¼øȯ ½Å°æ¸ÁÀÌ ¿ì¼öÇÑ ¼º´ÉÀ» º¸¿´À¸³ª, ´ÙÃþ ÆÛ¼ÁÆ®·ÐÀÌ ¹«¿ª ¼öÃâ °¡°Ý ¿¹Ãø¿¡¼ ´õ ¶Ù¾î³ ¼º´ÉÀ» º¸¿´´Ù. ÃßÈÄ Àå±â°£ µ¥ÀÌÅ͸¦ È®º¸ÇÑ´Ù¸é, ¼øȯ ½Å°æ¸Á ȤÀº Æ®·£½ºÆ÷¸Ó ±â¹Ý µö·¯´× ¸ðµ¨À» ÀÌ¿ëÇÏ¿© ´õ ¶Ù¾î³ ¼öÃâ °¡°Ý ¿¹ÃøÀÌ °¡´ÉÇÒ °ÍÀ¸·Î »ç·áµÈ´Ù. |
¿µ¹®³»¿ë (English Abstract) |
Korea Trade-Investment Promotion Agency (KOTRA) annually publishes the trade data in South Korea under the guidance of the Ministry of Trade, Industry and Energy in South Korea. The trade data usually contains Gross domestic product (GDP), a custom tariff, business score, and the price of export items in previous and this year, with regards to the trading items and the countries. However, it is challenging to figure out the meaningful insight so as to predict the future price on trading items every year due to the significantly large amount of data accumulated over the several years under the limited human/computing resources. Within this context, this paper proposes a multi layer perception that can predict the future price of potential trading items in the next year by training large amounts of past year¡¯s data with a low computational and human cost. |
Å°¿öµå(Keyword) |
KOTRA
ºòµ¥ÀÌÅÍ
»ê¾÷Åë»óÀÚ¿øºÎ
µö·¯´×
´ÙÃþ ÆÛ¼ÁÆ®·Ð
KOTRA
BigData
Ministry of Trade Industry and Energy
Deep Learning
Multi Layer Perception
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