Short-term prediction of the influent quantity time series of wastewater treatment plant based on a chaos neural network model

By predicting influent quantity, a wastewater treatment plant (WWTP) can be well controlled. The nonlinear dynamic characteristic of WWTP influent quantity time series was analyzed, with the assumption that the series was predictable. Based on this, a short-term forecasting chaos neural network model of WWTP influent quantity was built by phase space reconstruction. Reasonable forecasting results were achieved using this method.

[1]  J. Elsner,et al.  The weather attractor over very short timescales , 1988, Nature.

[2]  P. Grassberger,et al.  Measuring the Strangeness of Strange Attractors , 1983 .

[3]  J. Kurths,et al.  An attractor in a solar time series , 1987 .

[4]  Ramazan Gençay,et al.  Testing chaotic dynamics via Lyapunov exponents , 1998 .

[5]  R Hegger,et al.  Improved false nearest neighbor method to detect determinism in time series data. , 1999, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[6]  A. Wolf,et al.  Determining Lyapunov exponents from a time series , 1985 .

[7]  Ian Stewart,et al.  Mathematics: The Lorenz attractor exists , 2000, Nature.

[8]  A. Fowler,et al.  A correlation function for choosing time delays in phase portrait reconstructions , 1993 .

[9]  Andrew M. Fraser,et al.  Information and entropy in strange attractors , 1989, IEEE Trans. Inf. Theory.

[10]  Michael Small,et al.  Surrogate Test for Pseudoperiodic Time Series Data , 2001 .

[11]  M. Rosenstein,et al.  Reconstruction expansion as a geometry-based framework for choosing proper delay times , 1994 .

[12]  Schwartz,et al.  Singular-value decomposition and the Grassberger-Procaccia algorithm. , 1988, Physical review. A, General physics.

[13]  E. Lorenz.  Deterministic nonperiodic flow , 1963 .

[14]  Chi K. Tse,et al.  A Surrogate Test for Pseudo‐periodic Time Series Data , 2002 .

[15]  Vladimir N. Vapnik,et al.  The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.

[16]  P. P. Kanjilal,et al.  On the detection of determinism in a time series , 1999 .

[17]  M. Rosenstein,et al.  A practical method for calculating largest Lyapunov exponents from small data sets , 1993 .

[18]  J. Salas,et al.  Nonlinear dynamics, delay times, and embedding windows , 1999 .

[19]  A. Passamante,et al.  Using higher-order correlations to define an embedding window , 1991 .