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Ȩ Ȩ > ¿¬±¸¹®Çå > ±¹³» ³í¹®Áö > Çѱ¹Á¤º¸Åë½ÅÇÐȸ ³í¹®Áö (Journal of the Korea Institute of Information and Communication Engineering)

Çѱ¹Á¤º¸Åë½ÅÇÐȸ ³í¹®Áö (Journal of the Korea Institute of Information and Communication Engineering)

Current Result Document : 3 / 34 ÀÌÀü°Ç ÀÌÀü°Ç   ´ÙÀ½°Ç ´ÙÀ½°Ç

ÇѱÛÁ¦¸ñ(Korean Title) ¸ð¹ÙÀÏ ½º¸¶Æ® ÀåÄ¡ ¹èÅ͸®ÀÇ ³²Àº ½Ã°£ ¿¹Ãø¿¡ Àû¿ë °¡´ÉÇÑ Åë°è ±â¹ýµéÀÇ Æò°¡
¿µ¹®Á¦¸ñ(English Title) Performance Evaluation of Statistical Methods Applicable to Estimating Remaining Battery Runtime of Mobile Smart Devices
ÀúÀÚ(Author) Ź¼º¿ì   Sungwoo Tak  
¿ø¹®¼ö·Ïó(Citation) VOL 22 NO. 02 PP. 0284 ~ 0294 (2018. 02)
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(Korean Abstract)
¸ð¹ÙÀÏ ½º¸¶Æ® ÀåÄ¡ ¹èÅ͸®ÀÇ ³²Àº ½Ã°£ ¿¹Ãø¿¡ Åë°èÀû ±â¹ýÀÌ ¸¹ÀÌ »ç¿ëµÇ°í ÀÖ´Ù. ±×·¯³ª ƯÁ¤ Åë°è ±â¹ý¸¸À» »ç¿ëÇÑ ±âÁ¸ ¿¬±¸µéÀÇ °á°ú¸¸À¸·Î´Â, Åë°èÀû ±â¹ýÀÌ ¹èÅ͸®ÀÇ ³²Àº ½Ã°£ ¿¹Ãø¿¡ ÀûÇÕÇÑÁö°¡ ÆÇ´ÜÇϱ⠾î·Æ´Ù. ÀÌ¿¡ º» ³í¹®¿¡¼­´Â ½º¸¶Æ® ÀåÄ¡ ¹èÅ͸®ÀÇ ³²Àº ½Ã°£ ¿¹Ãø¿¡ Àû¿ë °¡´ÉÇÑ ´Ù¾çÇÑ Åë°è ±â¹ýµéÀÇ ¼º´ÉÀ» Æò°¡ÇÏ¿´´Ù. Æò°¡¿¡ »ç¿ëµÈ Åë°è ¿¹Ãø ±â¹ýÀº ´Ü¼ø ¹× À̵¿ Æò±Õ, ¼±Çü ȸ±Í, ´Ùº¯¼ö ÀûÀÀ ȸ±Í, ÀÚ±â ȸ±Í, ´ÙÇ×½Ä È¸±Í, ÀÌÁß ¹× »ïÁß Áö¼öÆòÈ° ±â¹ýÀÌ´Ù. ºÐ¼® °á°ú´Â, ÇâÈÄ Åë°èÀû ±â¹ýÀ» ¹èÅ͸® ³²Àº »ç¿ë ½Ã°£ ¿¹Ãø¿¡ Àû¿ëÇÏ·Á´Â IT ¿£Áö´Ï¾î¿¡°Ô Áß¿äÇÑ ÀÚ·á·Î È°¿ëµÉ ¼ö ÀÖ´Ù.
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(English Abstract)
Statistical methods have been widely used to estimate the remaining battery runtime of mobile smart devices, such as smart phones, smart gears, tablets, and etc. However, existing work available in the literature only considers a particular statistical method. Thus, it is difficult to determine whether statistical methods are applicable to estimating thr remaining battery runtime of mobile devices or not. In this paper, we evaluated the performance of statistical methods applicable to estimating the remaining battery runtime of mobile smart devices. The statistical estimation methods evaluated in this paper are as follows: simple and moving average, linear regression, multivariate adaptive regression splines, auto regressive, polynomial curve fitting, and double and triple exponential smoothing methods. Research results presented in this paper give valuable data of insight to IT engineers who are willing to deploy statistical methods on estimating the remaining battery runtime of mobile smart devices.
Å°¿öµå(Keyword) ½º¸¶Æ® ÀåÄ¡   Åë°èÀû ¹æ¹ý   ³²Àº »ç¿ë ½Ã°£ ¿¹Ãø   ȸ±Í ºÐ¼®   Smart devices   Statistical methods   Remaining battery runtime estimation   Regression analysis  
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