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Çѱ¹°Ç¼³°ü¸®ÇÐȸ / v.4, no.4, 2003³â, pp.192-200
½ÇÀûÀÚ·á ºÐ¼®¿¡ ÀÇÇÑ ÀûÁ¤ °ø»çºñ »êÁ¤¹æ¹ýÀÇ Àü»êÈ­ ¾Ë°í¸®Áò ±¸Ãà¿¡ °üÇÑ ¿¬±¸
( A Study on the Construction of Computerized Algorithm for Proper Construction Cost Estimation Method by Historical Data Analysis )
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º» ¿¬±¸´Â °ø°ø°Ç¼³ °ø»ç¿¡ ½ÇÀûÀÚ·á¿¡ ÀÇÇÑ °ø»çºñ»êÁ¤ ¹æ¹ýÀÇ Àü»êÈ­ Àû¿ëÀ» ¸ñÀûÀ¸·Î ¸ÕÀú ½ÇÀû°ø»çºñÀÇ Á¤ÀÇ ¹× ±¸Á¶¿Í ÇöÇà ½ÇÀû°ø»çºñ ¿î¿µÃ¼°è ÀÌÇØ¸¦ ÅëÇØ Àü»êÈ­ÀÇ ¹®Á¦Á¡ ¹× °³¼±±âÁØÀ» °ø»çºñ »êÁ¤¹æ¹ý Áß½ÉÀ¸·Î ºÐ¼® ±â¼úÇÏ¿´À¸¸ç Á¦¾ÈÇÑ ±âÁØ¿¡ µû¶ó Àü»êÈ­ ¾Ë°í¸®ÁòÀ» Á¦½ÃÇÏ¿´´Ù. ±âÁ¸ ¿¹Á¤°ø»çºñ »êÁ¤¹æ¹ýÀº ÀϹÝÀûÀÎ °øÁ¾º° ºÐ·ù¿¡ µû¸¥ ½ÇÀûÀÚ·áÁ¶°Ç°ú ´Ü¼øÈ÷ ¹°°¡Áö¼ö, ¿¬¸éÀû±Ô¸ð¿¡ µû¸¥ ½Ã°ø´Ü°¡¸¦ Àû¿ëÇÔÀ¸·Î¼­ °ø»çºñ»êÁ¤ÀÇ Á¤È®¼ºÀÌ ¿ä±¸µÇ¸ç, º» ¿¬±¸´Â ÀÌ¿¡ ´ëÇÑ °³¼± ¾ÈÀ¸·Î ºÎÀ§¿Í ºÎºÐº° °øÁ¾ºÐ·ù ¹æ½Ä¿¡ ÀÇÇÑ µ¥ÀÌÅÍ ÃßÃâÁ¶°ÇÀ¸·Î ½ÇÀûÀÚ·áÀÇ Àû¿ë¼º°ú ½Å·Ú¼ºÀ» ³ô¿´´Ù. ¶ÇÇÑ ¹°·®±Ô¸ð¿¡ ÀÇÇÑ °ø»çºñ º¯µ¿¿äÀÎÀ» ¹°·®±Ô¸ð ´ëºñ ´Ü°¡ÀÇ È®·üÀû ȸ±ÍºÐ¼®À¸·Î ¿¹Ãø ÃßÁ¤ÇÏ¿© ½ÇÇà °¡´ÉÇÑ ÀûÁ¤ °ø»çºñ »êÁ¤¹æ¹ýÀ» Á¦½ÃÇÏ¿´´Ù. µû¶ó¼­ º» ¿¬±¸¿¡¼­´Â Àü»êÈ­ Àû¿ë ¹æ¾ÈÀ¸·Î È®·üÀû ¿¹Á¤°ø»çºñ»êÁ¤¹æ¹ýÀ» ±âÁØÀ¸·Î ½Ã½ºÅÛ ÇÁ·Î¼¼½º¸¦ °¢ ¿µ¿ªº°·Î ±¸ÃàÇÏ°í ±×¿¡ µû¸¥ À©µµ¿ì ¾îÇø®ÄÉÀÌ¼Ç È°¿ë Åø°ú °³º° Àü»êÈ­¿¡ ´ëÇÑ ¾Ë°í¸®ÁòÀ» ±¸ÃàÇÏ¿´´Ù.
The object of this research is to develop a computerized algorithm of cost estimation method to forecast the total construction cost in the bidding stage by the historical and elemental work cost data. Traditional cost models to prepare Bill of Quantities in the korea construction industry since 1970 are not helpful to forecast the project total cost in the bidding stage because the BOQ is always constant data according to the design factors of a particular project. On the contrary, statistical models can provide cost quicker and more reliable than traditional ones if the collected cost data are sufficient enough to analyze the trends of the variables. The estimation system considers non-deterministic methods which referred to as the 'Monte Carlo simulation. The method interprets cost data to generate a probabilistic distribution for total costs from the deficient elemental experience cost distribution.
 
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½ÇÀûÀÚ·á;¸óÅ×Ä«¸¦·Î ½Ã¹Ä·¹À̼Ç;Ãʱâ´Ü°èºñ¿ë°ßÀû;°è¾à´Ü°è;historical cost data;Monte Carlo simulation;early stage cost estimation;bidding stage;
 
Çѱ¹°Ç¼³°ü¸®ÇÐȸ³í¹®Áý / v.4, no.4, 2003³â, pp.192-200
Çѱ¹°Ç¼³°ü¸®ÇÐȸ
ISSN : 2005-6095
UCI : G100:I100-KOI(KISTI1.1003/JNL.JAKO200320828321314)
¾ð¾î : Çѱ¹¾î
³í¹® Á¦°ø : KISTI Çѱ¹°úÇбâ¼úÁ¤º¸¿¬±¸¿ø
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