Abstract
Precise influent property forecasting is very important to maintain the stable operation of sewage treatment procedure. A big data analysis method of combining the wavelet packet transform (WPT) and adaptive network-based fuzzy inference system (ANFIS) is reported to solve this problem. In this approach, the WPT is used to decompose the influent property data in different cycles. The time sub-series, which are results of wavelet coefficients reconstruction, are employed to establish the forecasting system. The forecasting sub-results of each cycle are eventually integrated into an overall forecasting result. Furthermore, chaos theory is introduced to obtain the input structure of the multi-cycle regression models. The reported approach is verified by the historical influent property. A back propagation neural network and the standard ANFIS are used for a comparison test. The results demonstrate that the reported method has best ability in the peer models.
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