A course in fuzzy systems and control
A course in fuzzy systems and control
Perception-based approach to time series data mining
Applied Soft Computing
Fuzzy data mining for time-series data
Applied Soft Computing
Knowledge discovery in time series databases
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Self-organized fuzzy system generation from training examples
IEEE Transactions on Fuzzy Systems
Designing fuzzy inference systems from data: An interpretability-oriented review
IEEE Transactions on Fuzzy Systems
The WM method completed: a flexible fuzzy system approach to data mining
IEEE Transactions on Fuzzy Systems
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This paper aims to verify the capability of fuzzy inference system in establishing time series model for ship manoeuvrability. The traditional modeling approaches are usually based on a unified framework. Due to the presence of outliers or noises in ship sailing records, it is difficult in achieving satisfactory performance directly from data. In this paper, we propose a combined time series modeling method by the use of data mining technique and fuzzy system theory. Data mining concepts are introduced to improve the fuzzy rule extraction algorithm to make the resulting fuzzy inference system more robust with respect to the noises or outliers. A ship 20°/20° zig-zag test is simulated. The data point records in time series are obtained from an actual manoeuvring test. With comprehensive robustness analysis, our fuzzy inference system using data mining technology is proved to be a robust and accurate tool for ship manoeuvring simulation.