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Çѱ¹Áö¹Ý°øÇÐȸ / v.21, no.9, 2005³â, pp.25-34
ÃÖÀûÀÇ Àΰø½Å°æ¸Á ±¸Á¶ ¼³°è¸¦ ÅëÇÑ Áö¹Ý ¹°¼ºÄ¡ ÃßÁ¤
( Evaluation of Geotechnical Parameters Based on the Design of Optimal Neural Network Structure )
¹ÚÇüÀÏ;Ȳ´ëÁø;±Ç±âö;À̽·¡; »ï¼º¹°»ê(ÁÖ) °Ç¼³ºÎ¹® ±â¼ú¿¬±¸¼Ò;µ¿ÀÇ´ëÇб³ Åä¸ñ°øÇаú;»ï¼º¹°»ê(ÁÖ) °Ç¼³ºÎ¹® ±â¼ú¿¬±¸¼Ò;Çѱ¹°úÇбâ¼ú¿ø, °Ç¼³ ¹× ȯ°æ°øÇаú;
 
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º» ¿¬±¸¿¡¼­´Â ÃÖÀûÀÇ Àΰø½Å°æ¸Á ±¸Á¶ ¼³°è¸¦ À§ÇÏ¿© Àΰø½Å°æ¸Á°ú À¯ÀüÀÚ ¾Ë°í¸®ÁòÀÌ °áÇÕµÈ ½Å°æ¸Á±¸Á¶ ¼³°è±â¹ýÀÌ Á¦¾ÈµÇ¾ú´Ù. ÀúÀÚµéÀº ½Å°æ¸Á ±¸Á¶¼³°è½Ã ÀΰøÁö´É Àû¿ë¿¡ µû¸¥ °è»êÀûÀÎ º¹ÀâÇÔÀ» ÁÙÀ̸ç, ½Å°æ¸Á¿¡ ÀÇÇÑ ¿¹ÃøÀÇ Á¤È®¼ºÀ» Áõ°¡½Ã۱â À§ÇÏ¿© Àΰø½Å°æ¸Á°ú À¯ÀüÀÚ ¾Ë°í¸®ÁòÀÇ Æ¯¼ºÀ» Á¶ÇÕÇÏ¿´´Ù. ÃÖÀûÀÇ ½Å°æ¸Á ±¸Á¶¸¦ ¾ò±â À§ÇÏ¿© ½Å°æ¸Á ±¸Á¶ÀÇ ¼³°èº¯¼öµé¿¡ ´ëÇÑ À¯ÀüÀÚ ¼±º°±â¹ýÀ» Àû¿ëÇÏ¿´´Ù. Á¦¾ÈµÈ ÇÕ¼º ±â¹ýÀÇ Àû¿ë¼ºÀ» Æò°¡Çϱâ À§ÇÏ¿© ¿©·¯ Áö¹Ý°øÇÐ ¹°¼ºÄ¡µéÀ» ÃßÁ¤ÇÏ´Â ÇØ¼®¿¡ Àû¿ëµÇ¾ú´Ù.
This paper proposes a selection methodology composed of neural network (NN) and genetic algorithm (GA) to design optimal NN structure. We combine the characteristics of GA and NN to reduce the computational complexity of artificial intelligence applications and increase the precision of NN' prediction in the design of NN structure. Genetic selection approach of design parameters of NN is introduced to obtain optimal NN structure. Analyzed results for geotechnical problems are given to evaluate the performance of the proposed hybrid methodology.
 
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Artificial neural network;Genetic algorithm;Geotechnical parameter;Hybrid methodology;
 
Çѱ¹Áö¹Ý°øÇÐȸ³í¹®Áý / v.21, no.9, 2005³â, pp.25-34
Çѱ¹Áö¹Ý°øÇÐȸ
ISSN : 1229-2427
UCI : G100:I100-KOI(KISTI1.1003/JNL.JAKO200508824125368)
¾ð¾î : Çѱ¹¾î
³í¹® Á¦°ø : KISTI Çѱ¹°úÇбâ¼úÁ¤º¸¿¬±¸¿ø
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