Adaptive Inference-based Learning and Rule Generation Algorithms in Fuzzy Neural Network for Failure Prediction

Publisher:
IEEE
Publication Type:
Conference Proceeding
Citation:
The Proceedings of 2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2010), 2010, pp. 33 - 38
Issue Date:
2010-01
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highly desirable for decision makers and regulators in the finance industry. This study develops a new Failure Prediction (FP) approach which effectively integrates a fuzzy logic-based adaptive inference system with the learning ability of a neural network to generate knowledge in the form of a fuzzy rule base. This FP approach uses a preprocessing phase to deal with the imbalanced data-sets problem and develops a new Fuzzy Neural Network (FNN) including an adaptive inference system in the learning algorithm along with its network structure and rule generation algorithm as a means to reduce prediction error in the FP approach.
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