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- W2898893489 abstract "Dissolved oxygen(DO) directly affects the growth status of fishes in intensive aquaculture, thus we set up a prediction model to determine the future changing trend of dissolved oxygen. The DO prediction model we proposed through fusing and improving the self-adaptive differential evolution and relevance vector machine(SADE-RVM) in the paper. To evaluate and compare the performance of the SADE-RVM, the least squares support vector regression(LS-SVR), back propagation neural network(BP) and multivariate linear regression(MLR) model were used for comparison. The calculated mean absolute percentage errors of the results of the four prediction models were 0.35%, 1.3%, 2.03% and 1.33%, respectively. The SADE-RVM model has a higher prediction accuracy and more reliable performance than the other models. When the predicted values of dissolved oxygen fall below the safety level, the farmer can start an oxygen increasing machine in advance to maintain the safety of fishes. The prediction model was used in Yangzhong, Jiangsu province, China, and it performed well and helped farmers make decisions and reduce aquaculture risks." @default.
- W2898893489 created "2018-11-09" @default.
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- W2898893489 date "2018-08-11" @default.
- W2898893489 modified "2023-09-26" @default.
- W2898893489 title "Prediction Model of Dissolved Oxygen Based on SADE-RVM" @default.
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- W2898893489 doi "https://doi.org/10.1145/3265639.3265661" @default.
- W2898893489 hasPublicationYear "2018" @default.
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