Integration of connectionist methods and chaotic time-series analysis for the prediction of process data
R. Kozma, Nikola Kirilov Kasabov, Jeyoong Kim, A. Cohen · International Journal of Intelligent Systems · 1998
A connectionist-based time-series analysis method is described that includes chaotic characterization, fractal analysis together with statistical data processing in an adaptive fuzzy neural network environment. The applied fuzzy neural network (FuNN) can utilize as well as generate knowledge during an iterative learning and adaptation procedure. Two major aspects of the present work are (1) incorporating knowledge into the fuzzy neural network based on the nonlinear deterministic, chaotic analysis of the signals and (2) refining and updating the knowledge base by the FuNN using adaptive learning techniques. Examples include the standard gas-furnace benchmark data analysis and also an application to a case study of multivariate signal analysis as part of a project for establishing a plantwise monitoring and process control system. © 1998 John Wiley & Sons, Inc.