Water quality fluctuating range prediction method based on combination of deep learning algorithm and mixed integer linear programming
A mixed integer and linear programming technology, applied in forecasting, calculation, data processing applications, etc., can solve problems such as difficult to establish water quality prediction models
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[0031] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.
[0032] The overall flow chart of the water quality fluctuation interval prediction method based on the combination of deep learning algorithm and mixed integer linear programming is as follows: figure 1 shown, including the following steps:
[0033] Step 1. Historical data preprocessing of water quality indicators
[0034] The prediction of water quality indicators is a time series prediction problem. The lack of data at any point in time will affect the accuracy of the overall prediction to a certain extent. Therefore, it is necessary to complete the historical data of water quality monitoring. According to the known data before and after the missing point, the fitting polynomial is constructed by the method of least squares, and then the missing value of the historical data of water quality indicators is supplemented according to thi...
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