Learning Interval-Valued Fuzzy Cognitive Maps with PSO Algorithm for Abnormal Stock Return Prediction

2017 ◽  
pp. 113-125 ◽  
Author(s):  
Petr Hajek ◽  
Ondrej Prochazka
Keyword(s):  
Stock Return ◽  
Cognitive Maps ◽  
Pso Algorithm ◽  
Fuzzy Cognitive Maps ◽  
Stock Return Prediction ◽  
Interval Valued

scholarly journals Interval-valued fuzzy cognitive maps with genetic learning for predicting corporate financial distress

Filomat ◽  
2018 ◽  
Vol 32 (5) ◽  
pp. 1657-1662 ◽  
Author(s):  
Petr Hajek ◽  
Ondrej Prochazka
Keyword(s):  
Financial Distress ◽  
Causal Reasoning ◽  
Mean Squared Error ◽  
Nonlinear Problems ◽  
Cognitive Maps ◽  
Fuzzy Cognitive Maps ◽  
Squared Error ◽  
Neuro Fuzzy ◽  
Model Complex ◽  
Interval Valued

Fuzzy cognitive maps (FCMs) integrate neural networks and fuzzy logic to model complex nonlinear problems through causal reasoning. Interval-valued FCMs (IVFCMs) have recently been proposed to model additional uncertainty in decision-making tasks with complex causal relationships. In traditional FCMs, optimization algorithms are used to learn the strengths of the relationships from the data. Here, we propose a novel IVFCM with real-coded genetic learning. We demonstrate that the proposed method is effective for predicting corporate financial distress based on causally connected financial concepts. Specifically, we show that this method outperforms FCMs, fuzzy grey cognitive maps and adaptive neuro-fuzzy systems in terms of root mean squared error.

scholarly journals Ensemble Interval-Valued Fuzzy Cognitive Maps

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 38356-38366 ◽  
Author(s):  
Jingping Wang ◽  
Qing Guo
Keyword(s):  
Cognitive Maps ◽  
Fuzzy Cognitive Maps ◽  
Interval Valued
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