2018³â Ãß°èÇмú´ëȸ
Current Result Document :
ÇѱÛÁ¦¸ñ(Korean Title) |
IoT ȯ°æ¿¡¼ÀÇ È¿À²ÀûÀÎ LSTM ±¸¼º |
¿µ¹®Á¦¸ñ(English Title) |
Efficient LSTM Configuration in IoT Environment |
ÀúÀÚ(Author) |
ÀÌÁ¾¿ø
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Jongwon Lee
Chulhyun Hwang
Sungock Lee
Hyunok Song
Hoekyung Jung
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¿ø¹®¼ö·Ïó(Citation) |
VOL 22 NO. 02 PP. 0345 ~ 0345 (2018. 10) |
Çѱ۳»¿ë (Korean Abstract) |
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¿µ¹®³»¿ë (English Abstract) |
Internet of Things (IoT) data is collected in real time and is treated as highly reliable data because of its high precision. However, IoT data is not always highly reliable data. Because, data be often incomplete values for reasons such as sensor aging and failure, poor operating environment, and communication problems. So, we propose the methodology for solve this problem. Our methodology implements multiple LSTM networks to individually process the data collected from the sensors and a single LSTM network that batches the input data into an array. And, we propose an efficient method for constructing LSTM in IoT environment.
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Å°¿öµå(Keyword) |
Data Quality
IoT
Deep Learning
Recurrent Neural Network
LSTM
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ÆÄÀÏ÷ºÎ |
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