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

摘要：

Creating an applicable and precise failure prediction system is 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.

作者: Vahid Behbood Jie lu Guangquan Zhang

作者单位: Decision Systems & E-Service Intelligence Research Laboratory Center for Quantum Computing and Intelligent System, School of Software Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, POBOX123, Broadway, NSW2007, Australia

会议类型: 国际会议

会议名称: The 2010 International Conference on Intelligent Systems and Knowledge Engineering(第五届智能系统与知识工程国际会议)

会议地点: 杭州

会议语种:英文

页码: 33-38

在线出版日期: 2010-11-15（万方平台首次上网日期，不代表论文的发表时间）