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광학센서를 이용한 강우정보 생산기법 개발 (최적 강우강도 기법을 이용한 실시간 강우정보 산정) KCI 등재
Development of Rainfall Information Production Technology Using Optical Sensors (Estimation of Real-Time Rainfall Information Using Optima Rainfall Intensity Technique)
pp.1101-1111
In this paper, among the W-S-R relationship methods proposed by Lee, et. al., (2020) to produce rain-based rain information in real time, we tried to produce actual rain information by applying machine learning techniques to take into account the effects of wiper operation. To this end, rain sensor proposed the Graded Descent and Threshold Map method for pre-processing the cumulative value of the difference before and after wiper operation by utilizing four sensitive channels for optical sensors developed by Kim Byung-sik (2016) and using rain sensor data produced by five rain conditions in indoor artificial rainfall experiments. This method is the method of producing rainfall information by calculating the average value of the Threshold according to the rainfall conditions and channels, creating a Threshold Map corresponding to the grid 4 (channel) x 5 (thinking of rainfall information) and applying Optima Rainfall Intensity among the big data processing techniques. For the verification of these proposed findings, the application was evaluated by comparing the rainfall observations with the methods presented by Lee, et. al., (2020).
1. 서 론
2. 연구방법
2.1. 레인센서를 이용한 실내실험
2.2. 머신러닝 기법을 이용한 레인센서 자료 전처리
3. 적용 및 결과
3.1. Gradient Descent 알고리즘 적용
3.2. 실외 강우 관측을 통한 W-S-R 관계식 검증
4. 결론 및 고찰
REFERENCES
