A Review on Modeling Techniques in Chaotic Soft Computing Systems using Forecasting

Time series prediction finds various applications in medicine, stock market, meteorology, geology, astronomy, chemistry, biometrics and robotics. In this paper we give a review on various modeling techniques in soft computing for various weather applications in presence of chaos if any. There are various prediction models which enhance the ability to reduce the after effects of the hazards created by such uncertainty. In local modeling approaches, the independent models which work on different nonlinear systems and processes are very successful in modeling, identification, and prediction applications. The results of such reviews of various methodologies are to get an efficient analogy to create a much better prediction model for chaotic neuro fuzzy or adaptive neural network systems.