Title :
Chaos-characteristic analysis of Sewage inward-flow quantity data based on the maximal Lyapunov index analysis and the methods of substitution
Author_Institution :
Coll. of Econ. & Manage., Hebei Univ. of Sci. & Technol., Shijiazhuang, China
Abstract :
This article conducts the research in view of the chaos characteristic of inward flow quantity data in sewage treatment plant. During the research, we put to use small sampling time: taus = 1 h, to avoid losing some partial information in the primary signal. First, we calculate the Lyapunov´s maximal index to determine the chaos characteristics of time sequence based on the phase space restructuring foundation. Then there will be the CRP analysis to the sewage time series. At last, by using the substitution data law, we can eliminate the possibility that time series is quasi periodic, and we can get the conclusion that the time series of contaminated water volume is deterministic system produced by nonlinear dynamics.
Keywords :
Lyapunov methods; chaos; sewage treatment; time series; chaos characteristic analysis; maximal Lyapunov index analysis; phase space restructuring foundation; sewage inward flow quantity data; sewage treatment plant; substitution data law; time series; Chaos; Cybernetics; Delay effects; Machine learning; Predictive models; Sampling methods; Sewage treatment; Stochastic processes; Time series analysis; Water pollution; Chaos; Lyapunov´s maximal index; Substitution data analysis; Time sequence;
Conference_Titel :
Machine Learning and Cybernetics, 2009 International Conference on
Conference_Location :
Baoding
Print_ISBN :
978-1-4244-3702-3
Electronic_ISBN :
978-1-4244-3703-0
DOI :
10.1109/ICMLC.2009.5212639