Eriocheir sinensis should cultivate in high water quality ponds, which is affected by many combined factors such as physics, chemistry, biology etc. Using the real-time water quality monitoring historical data to test one of the water quality indexes and predict this index in the next time has great significance. The dissolved oxygen is one of the most important indexes in aquaculture, such as in the Eriocheir sinensis pond. This paper established a dissolved oxygen prediction model of water quality monitoring system based on BP neural network. The forecast data which is predicted by the established model could fit the actual monitoring data very well.
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