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Current Result Document :
ÇѱÛÁ¦¸ñ(Korean Title) |
µµ½ÃÀα¸ºÐÆ÷¸ðÇü °³¹ßÀ» À§ÇÑ GA¸ðÇü°ú ȸ±Í¸ðÇüÀÇ ÀûÇÕ¼º ºñ±³¿¬±¸ |
¿µ¹®Á¦¸ñ(English Title) |
A Comparative Study on the Genetic Algorithm and Regression Analysis in Urban Population Surface Modeling |
ÀúÀÚ(Author) |
ÃÖ³»¿µ
Nae-Young Choei
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¿ø¹®¼ö·Ïó(Citation) |
VOL 18 NO. 05 PP. 0107 ~ 0117 (2010. 12) |
Çѱ۳»¿ë (Korean Abstract) |
º» ¿¬±¸´Â ÃÖ±Ù ´Ù¼ö µµ½Ã°³¹ß»ç¾÷µéÀÌ È°¹ßÈ÷ ÁøÇàµÇ°í Àִ ȼº½Ã µ¿ºÎ±ÇÀ» »ç·Ê´ë»óÁö·ÎÇÏ¿© ÇàÁ¤±¸¿ª ´ÜÀ§ Àα¸µ¥ÀÌÅ͸¦ °ÝÀÚÇü Àα¸ºÐÆ÷ÀÚ·á·Î º¯È¯ÇÑ ÈÄ Àα¸À¯ÀÎÀ» À¯¹ßÇÒ °ÍÀ¸·Î ¿¹»óµÇ´Â ÁÖ¿ä µµ½Ã°èȹ°ü·Ã °ø°£º¯¼öµéÀ» GIS·Î ÃøÁ¤ ´ëÀÔÇÏ¿© Á¦³×ƽ ¾Ë°í¸®Áò±â¹ý°ú ȸ±ÍºÐ¼®±â¹ý µÎ °¡Áö ¹æ¹ýÀ¸·Î ÀÏÁ¾ÀÇ µµ½ÃÀα¸ºÐÆ÷¸ðÇüÀ» ±¸ÃàÇÏ¿´´Ù. µÎ °¡Áö ¸ðÇüÀÇ ºÐ¼®°á°ú¸¦ ÅëÇØ µµ½Ãȯ°æ Çؼ®¿¡ ÀÖ¾î¼ÀÇ µÎ ±â¹ýÀÇ ¼º´É»ó ƯÀåÁ¡À» ºñ±³ÇØ º¸¾ÒÀ¸¸ç, ºÐ¼®°á°ú GA±â¹ýÀº º¯¼ö ¼³¸í·Â¿¡ °üÇÑ º¯º°·Â¿¡ ÀÖ¾î ÀϹÝȸ±ÍºÐ¼®º¸´Ù ¿ì¿ùÇÑ Æ¯Â¡ÀÌ ÀÖÀ½À» ¾Ë ¼ö ÀÖ¾ú°í µû¶ó¼ ȸ±ÍºÐ¼®°ú º´ÇàÇÒ °æ¿ì ¸Å¿ì Á÷°üÀûÀÌ¸ç º¸¿ÏÀûÀÎ µµ½ÃºÐ¼®±â¹ýÀÌ µÉ ¼ö ÀÖÀ½À» È®ÀÎÇÒ ¼ö ÀÖ¾ú´Ù.
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¿µ¹®³»¿ë (English Abstract) |
Taking the East-Hwasung area as the case, this study first builds gridded population data based on the municipal population survey raw data, and then measures, by way of GIS tools, the major urban spatial variables that are thought to influence the composition of the regional population. For the purpose of comparison, the urban models based on the Genetic Algorithm technique and the regression technique are constructed using the same input variables. The findings indicate that the GA output performed better in differentiating the effective variables among the pilot model variables, and predicted as much consistent and meaningful coefficient estimates for the explanatory variables as the regression models. The study results indicate that GA technique could be a very useful and supplementary research tool in understanding the urban phenomena.
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Å°¿öµå(Keyword) |
Á¦³×ƽ ¾Ë°í¸®Áò
ÀϹÝȸ±ÍºÐ¼®
´Ü°èÀû ȸ±ÍºÐ¼®
µµ½ÃÀα¸ºÐÆ÷¸ðÇü
ÀûÇÕ¼º ÇÔ¼ö
Genetic Algorithm
Regression
Stepwise Regression
Population Surface Model
Fitness Function
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