Hybrid CRO Based FLANN for Financial Credit Risk Forecasting

  • S. R. Sahu
  • D. P. Kanungo
  • H. S. Behera
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 31)


Modern financial market has become capable enough to provide its services to a large number of customers simultaneously. On the other hand, the exponential hike in financial crises per year has uplifted the demand for precise and potential classifier models. In this work a hybrid model of clustering and neural network based classifier has been proposed, i.e. FCM-FLANN-CRO. Three financial credit risk data sets were applied to the processing and the model is evaluated using the performance metrics such as RMSE and Accuracy. The experimental result shows the proposed model outperforms its MLP counterpart and other two non-hybrid models. The proposed model provides its best result with 97.05 % of classification accuracy.


Classification Functional link artificial neural network (FLANN) Multilayered perceptron (MLP) Credit risk forecasting Chemical reaction optimization (CRO) Clustering Fuzzy C-means (FCM) 


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Copyright information

© Springer India 2015

Authors and Affiliations

  1. 1.Department of Computer Science Engineering and Information TechnologyVeer Surendra Sai University of TechnologyBurlaIndia

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