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Çѱ¹¼öÀÚ¿øÇÐȸ / v.38, no.6, 2005³â, pp.439-448
Wavelet TransformÀ» ÀÌ¿ëÇÑ ¼ö¹®½Ã°è¿­ ºÐ¼®
( Analysis of Hydrologic Time Series Using Wavelet Transform )
±ÇÇöÇÑ;¹®¿µÀÏ; ;¼­¿ï½Ã¸³´ëÇб³ Åä¸ñ°øÇаú;
 
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º» ³í¹®Àº ¼ö¹®½Ã°è¿­¿¡¼­ ³ªÅ¸³ª´Â Áֱ⼺ ¹× °æÇ⼺ µîÀ» Æò°¡Çϱâ À§ÇÑ ¹æ¹ýÀ¸·Î Fourier TransformÀ» °³¼±ÇÑ Wavelet Transform¹æ¹ýÀ» Á¦½ÃÇϰí ÀÌ¿¡ ´ëÇÑ Å¸´ç¼º ¹× Àû¿ë¼ºÀ» ¿ù°­¼ö·® ¹× ¿¬°­¼ö·® ÀÚ·á¿Í ´ëÇ¥ÀûÀÎ ±â»óÀÎÀÚÀÎ ³²¹æÁøµ¿Áö¼ö(SOI)¿Í ÇØ¼ö¸é¿Âµµ(SST)¸¦ ´ë»óÀ¸·Î Æò°¡ÇØ º¸¾Ò´Ù. Fourier TransformÀº ½Ã°£ÀûÀΠƯ¼ºÀ» ÆÄ¾ÇÇÏÁö ¸øÇÏ´Â ¹Ý¸é¿¡ Wavelet TransformÀº ¼ö¹®½Ã°è¿­ÀÌ °®´Â ½Ã°£ÀûÀΠƯ¼ºÀ» À¯ÁöÇϸ鼭 ºóµµ¿¡ ´ëÇÑ ½ºÆåÆ®·³À» º¸´Ù È¿À²ÀûÀ¸·Î Æò°¡ÇÒ ¼ö ÀÖ¾ú´Ù. Wavelet TransformÀ» ÀÌ¿ëÇÏ¿© ºÐ¼®ÇÑ °á°ú ±¹³» ¿ù°­¼ö·®Àº 1³âÀ» Áß½ÉÀ¸·Î °­ÇÑ ½ºÆåÆ®·³À» ³ªÅ¸³»°í ÀÖÀ¸¸ç ¿¬°­¼ö·®Àº 2-8³â Áֱ⿡¼­ Åë°èÀûÀ¸·Î À¯ÀÇÇÑ Áֱ⸦ È®ÀÎÇÒ ¼ö ÀÖ¾ú´Ù. SOI¿Í SST¿¡¼­´Â 2-8³â ÁֱⰡ Áö¹èÀûÀÓÀ» È®ÀÎÇÒ ¼ö ÀÖ¾ú´Ù.
This paper introduces the wavelet transform that was improved by the fourier transform to assess periodicities and trends, we assessed propriety with examples of two monthly precipitation data, annual precipitation, SOI index and SST index. The wavelet transform can effectively assess the power spectrum corresponding to frequency as maintaining chronological characteristics. The results of the analysis using the wavelet transform showed that the monthly precipitation have the strongest power spectrum near that of 1 year, and the annual precipitation represent the dominated spectrum in the band of 2-8 years. Also, the SOI index and SST index indicate the strongest power spectrum in the band of 2-8 years.
 
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½ºÆåÆ®·³;½Ã°è¿­;fourier transform;wavelet transform;spectrum;time series;
 
Çѱ¹¼öÀÚ¿øÇÐȸ³í¹®Áý / v.38, no.6, 2005³â, pp.439-448
Çѱ¹¼öÀÚ¿øÇÐȸ
ISSN : 1226-6280
UCI : G100:I100-KOI(KISTI1.1003/JNL.JAKO200531234554576)
¾ð¾î : Çѱ¹¾î
³í¹® Á¦°ø : KISTI Çѱ¹°úÇбâ¼úÁ¤º¸¿¬±¸¿ø
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