Intelligent financial time series forecasting: A complex neuro-fuzzy approach with multi-swarm intelligence - Li, Chunshien; Chiang, Tai-Wei (Zielona Góra: Uniwersytet Zielonogórski)
Financial investors often face an urgent need to predict the future. Accurate forecasting may allow investors to be aware of changes in financial markets in the future, so that they can reduce the risk of investment. In this paper, we present an intelligent computing paradigm, called the Complex Neuro-Fuzzy System (CNFS), applied to the problem of financial time series forecasting.
Keywords: complex fuzzy set; complex neuro-fuzzy system; hierarchical multi-swarm particle swarm optimization; recursive least squares estimator; time series forecasting