All Issue

2021 Vol.63, Issue 5 Preview Page
2021. pp. 83-93
Abstract
References

REFERENCES

1
M. R. Gu, K. S. Lee and D. S. Kang, Journal of the Korean Institute of Information Technology, Image noise reduction using modified gaussian filter by estimated standard deviation of noise, 8(12); 111-117, (in Korean) (2010)
2
M. Kim, J. Y. Choi, J. H. Bang and J. J. Lee, Journal of the Korean Society of Agricultural Engineers, Outlier detection of real-time reservoir water level data using threshold model and artificial neural network model, 61(1); 107-120, (in Korean) (2019)
3
C. S. Kim, H. S. Kim, H. S. Cho and H. R. Kim, Journal of the Korea Water Resources Association, Establishment of national quality control system for the hydrologic data; 1823-1827, (in Korean) (2008)
4
KMA, Real-time quality control system for meteorological observation data (I) Application, 11-1360000 -000206-01 (Tech. Note 2006-2): 157 (in Korean) (2006)
5
Korea Rural Community Corporation (KRC), Development of technology for securing reliability of water level measurement data and estimating water supply, (in Korean) (2018)
6
Korea Rural Community Corporation (KRC), A study on the establishment of quality control standards for hydrologic data in agricultural reservoirs and waterways, (in Korean) (2019)
7
Korea Rural Community Corporation (KRC), Advanced quality management study of reservoir water level measurement data, (in Korean) (2020)
8
K-water, K-water data quality management guidelines (water information), (in Korean) (2018)
9
J. S. Lee, Hydrology; 305, (in Korean) (2006)10.5124/jkma.2006.49.4.305
10
J. S. Lee, Hydrology, 447(480), (in Korean) (2006)10.1016/0022-1694(70)90247-7
12
Ministry of Agriculture, Food and Rural Affairs, Development of information analysis technology for abnormal behavior of agricultural reservoirs using big data related to weather information and water levels, (in Korean) (2016)
13
Ministry of Environment, Environment and maintenance and management of hydrologic research facilities and standards for quality management of hydrologic data, (in Korean) (2018)
14
Ministry of the Interior and Safety, Public data quality management manual ver 2.0, (in Korean) (2018)
15
Ministry of Land, Transport and Maritime Affairs, Establishment of a basic plan for hydrologic investigation (2010-2019), (in Korean) (2008)
16
Ministry of Land, Transport and Maritime Affairs, The 4th Comprehensive Plan for Water Resources 2nd Amendment (2011-2020), (in Korean) (2011)
17
Ministry of Land, Infrastructure and Transport, Establishment and operation of the national hydrologic data quality management system (7th), (in Korean) (2018)
18
J. W. Oh, J. H. Park and Y. K. Kim, Journal of the Korea Water Resources Association, Missing hydrological data estimation using neural network and real time data reconciliation, 41(10); 1059-1065, (in Korean) (2008)10.3741/jkwra.2008.41.10.1059
19
H. J. Shin and T. H. Lee, Journal of the Korea Water Resources Association, A study on the estimation of missing hydrological data using adaptive network-based fuzzy inference system (ANFIS); 1738-2726 (2020)
20
M. H. Yang, W. H. Nam, H. J. Kim, T. G. Kim, A. K. Shin and M. S. Kang, Journal of the Korean Society of Hazard Mitigation, Anomaly detection in reservoir water level data using the LSTM model based on deep learning, 21(1); 71-81, (in Korean) (2020)10.9798/kosham.2021.21.1.71
Information
  • Publisher :The Korean Society of Agricultural Engineers
  • Publisher(Ko) :한국농공학회
  • Journal Title :Journal of Korean Society of Agricultural Engineers
  • Journal Title(Ko) :한국농공학회논문집
  • Volume : 63
  • No :5
  • Pages :83-93
  • Received Date : 2021-05-26
  • Revised Date : 2021-06-01
  • Accepted Date : 2021-09-17