The paper focuses on the application of fuzzy cognitive map (FCM) with multi-step learning algorithms based on gradient method and Markov model of gradient for prediction tasks. Two datasets were selected for the implementation of the algorithms: real data of household electricity consumption and stock exchange returns that include Istanbul Stock Exchange returns. These data were used in learning and testing processes of the proposed FCM approaches. A comparative analysis of the two-stepmethod of Markov model of gradient,multi-step gradient method and one-step gradient method is performed in order to show the capabilities and effectiveness of each method and conclusions are based on the obtained MSE, RMSE, MAE and MAPE errors.
CITATION STYLE
Papageorgiou, E. I., Poczęta, K., Yastreboz, A., & Laspidou, C. (2015). Fuzzy cognitive maps and multi-step gradient methods for prediction: Applications to electricity consumption and stock exchange returns. In Smart Innovation, Systems and Technologies (Vol. 39, pp. 501–511). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-319-19857-6_43
Mendeley helps you to discover research relevant for your work.