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기상데이터를 활용한 유수식 양식장 용존산소량 예측 시스템 구현
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- Issue Date
- 2024-06
- Citation
- 대한전자공학회 학술 대회 (하계) 2024, pp.2257-2261
- Publisher
- 대한전자공학회
- Language
- Korean
- Type
- Conference Paper
- Abstract
- Water quality is crucial in aquaculture, and maintaining it typically requires an oxygen supply system, which can be costly due to its electronic components. To address this issue, we have developed the Water Quality Prediction Application that automatically adjusts oxygen supply amount. This system forecasts water quality after specified time intervals (e.g. 30 minutes, 1hour) using data collected every minute. In order to predict this well, we preprocess this data into 𝑅SUP𝜏×𝑐/SUP matrices, where 𝜏 is the set time interval and 𝑐 represents the number of columns in the merged dataset, which combines fish farm data with maritime climate data. To validate our approach that merged two datasets, we proposed experiments to compare two models : one trained using data from fish tanks alone, and another trained using both fish tank data and climate data.
- KSP Keywords
- Climate data, Data collected, Electronic components, Fish tank, Oxygen supply, Prediction application, Supply System, Time interval, Water quality prediction