• Àüü
  • ÀüÀÚ/Àü±â
  • Åë½Å
  • ÄÄÇ»ÅÍ
´Ý±â

»çÀÌÆ®¸Ê

Loading..

Please wait....

Çмú´ëȸ ÇÁ·Î½Ãµù

Ȩ Ȩ > ¿¬±¸¹®Çå > Çмú´ëȸ ÇÁ·Î½Ãµù > Çѱ¹Á¤º¸Åë½ÅÇÐȸ Çмú´ëȸ > 2015³â Ãá°èÇмú´ëȸ

2015³â Ãá°èÇмú´ëȸ

Current Result Document : 7 / 7

ÇѱÛÁ¦¸ñ(Korean Title) ±â°èÇнÀÀ» ÀÌ¿ëÇÑ °¡Ãà Áúº´ Á¶±â ¹ß°ß ¹æ¾È
¿µ¹®Á¦¸ñ(English Title) Fast Detection of Disease in Livestock based on Machine Learning
ÀúÀÚ(Author) ÀÌ¿õ¼·   Woongsup Lee   Sewoon Hwang   Jonghyun Kim  
¿ø¹®¼ö·Ïó(Citation) VOL 19 NO. 01 PP. 0294 ~ 0297 (2015. 05)
Çѱ۳»¿ë
(Korean Abstract)
ÃÖ±Ù ±â°èÇнÀ¿¡ ±â¹ÝÀ» µÐ ºòµ¥ÀÌÅÍ ºÐ¼®ÀÌ Å« °ü½ÉÀ» ¹ÞÀ¸¸é¼­ ´Ù¾çÇÑ Çй® ºÐ¾ß¿¡ ±â°è ÇнÀ¹æ¾ÈµéÀÌ Á¢¸ñµÇ°í ÀÖ´Ù. ±× ´ëÇ¥ÀûÀÎ ºÐ¾ß Áß Çϳª·Î ³óÃà»ê ºÐ¾ß¸¦ µé ¼ö ÀÖ°í ½ÇÁ¦ ´Ù¾çÇÑ ±â°èÇнÀ ¹æ¾ÈµéÀÌ ³óÃà»êºÐ¾ß¿¡ Àû¿ëµÇ°í ÀÖ´Ù. ÇÏÁö¸¸ ³óÃà»ê¿¡¼­ È°¿ëµÇ´Â ±â°èÇнÀÀÇ °æ¿ì ´ëºÎºÐ ³ó¾÷ºÐ¾ßÀÇ ±âÈÄ¿¹Ãø ¹× Ãà»êºÐ¾ßÀÇ À¯ÀüÀÚ ºÐ¼® ÂÊÀ¸·Î ¿¬±¸°¡ ÁýÁߵǾîÀÖ°í, °¡ÃàÀÇ »ýü µ¥ÀÌÅ͸¦ È°¿ëÇÑ ±â°èÇнÀ ¹æ¾ÈÀº ¸¹Àº ¿¬±¸°¡ ÀÌ·ç¾îÁöÁö ¾Ê¾Ò´Ù. º» ¿¬±¸¿¡¼­´Â °¡ÃàÀÇ ½Ç½Ã°£ »ýü µ¥ÀÌÅ͸¦ ÀÌ¿ëÇÏ¿© ¹®Á¦°¡ ¹ß»ýÇÑ °³Ã¼¸¦ Á¶±â¿¡ ¹ß°ßÇÏ´Â ¹æ¾ÈÀ» Á¦¾ÈÇÏ¿´´Ù. Á¦¾È ¹æ¾È¿¡¼­´Â ±â´ñ°ª ÃÖ´ëÈ­ ¾Ë°í¸®ÁòÀ» ÀÌ¿ëÇÏ¿© ´ÜÀÏ °¡Ãà °³Ã¼µéÀÇ ½Ç½Ã°£ »ýü µ¥ÀÌÅ͸¦ 2°³ÀÇ Å¬·¯½ºÅÍ·Î ³ª´©°í ÀÌ µÎ Ŭ·¯½ºÅÍ »çÀÌÁîÀÇ º¯È­¸¦ ÅëÇؼ­ ÀÌ»ó °³Ã¼¸¦ Á¶±â¿¡ ÆÇ´ÜÇÑ´Ù. ƯÈ÷ ´ÜÀÏ °³Ã¼ÀÇ ¹®Á¦¿Í Àü¿°¼º Áúº´ ¿©ºÎ¸¦ ³ª´©¾î ÆÇ´ÜÇϹǷΠ±¸Á¦¿ª°ú °°Àº Àü¿°¼º Áúº´ÀÇ °æ¿ì ºü¸¥ ´ëÀÀÀ» °¡´ÉÄÉ ÇÏ¿© ±¹°¡Àû ¼Õ½ÇÀ» ÁÙÀÏ ¼ö ÀÖ°Ô ÇÑ´Ù. ´õºÒ¾î Á¦¾È ¹æ¾ÈÀº ÃøÁ¤ »ýü µ¥ÀÌÅÍ¿¡ ´ëÇÑ Åë°èÀû Á¤º¸ ¾øÀ̵µ ÀûÀÀÀûÀ¸·Î Ŭ·¯½ºÅ͸¦ Çü¼ºÇÒ ¼ö ÀÖÀ¸¹Ç·Î Ãà»ç ¿ÜºÎÀÇ È¯°æ ¿ä¼Ò¿¡ ÀÇÇؼ­ »ýü µ¥ÀÌÅÍÀÇ Åë°èÀû Ư¼ºÀÌ º¯È­´Â »óȲ¿¡¼­µµ ÀûÀÀÀûÀ¸·Î µ¿ÀÛÇÒ ¼ö ÀÖ´Ù.

¿µ¹®³»¿ë
(English Abstract)
Recently, big data analysis which is based on machine learning has been gained a lot of attentions in various fields. Especially, agriculture is considered as one promising field that machine learning algorithm can be efficiently utilized and accordingly, lots of works have been done so far. However, most of the researches are focusing on the forecast of weather or analysis of genome, and machine learning algorithm for livestock management, especially which uses individual data of livestocks, e.g., temperature and movement, are not properly investigated yet. In this work, we propose fast abnormal livestock detection algorithm based on machine learning, more specifically expectation maximization, such that livestock which has problem can be efficiently and promptly found. In our proposed scheme, livestocks are divided into two clusters using expectation maximization based on their bionic data and the abnormal livestock can be detected by comparing the size of two clusters. Especially, we divide the case in which single livestock has problem and the case in which livestocks have epidemic such that fast response is enabled when epidemic case. Moreover, our algorithm does not need statistical information.
Å°¿öµå(Keyword) ±â°èÇнÀ   Ãà»ê   ºòµ¥ÀÌÅÍ   Áúº´ Á¶±â ¹ß°ß   Àü¿°¼º Áúº´  
ÆÄÀÏ÷ºÎ PDF ´Ù¿î·Îµå