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Fuzzy Inference System Design Based on Data Mining Concepts and Its Application in Time Series Forecasting
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作者 白一鸣 赵永生 范云生 《Journal of Donghua University(English Edition)》 EI CAS 2016年第5期809-813,共5页
This paper adopts data mining(DM) technique and fuzzy system theory for robust time series forecasting.By introducing DM technique,the fuzzy rule extraction algorithm is improved to be more robust with the noises and ... This paper adopts data mining(DM) technique and fuzzy system theory for robust time series forecasting.By introducing DM technique,the fuzzy rule extraction algorithm is improved to be more robust with the noises and outliers in time series.Then,the constructed fuzzy inference system(FIS) is optimized with a partition refining strategy to balance the system's accuracy and complexity.The proposed algorithm is compared with the WangMendel(WM) method,a benchmark method for building FIS,in comprehensive analysis of robustness.In the classical Mackey-Glass time series forecasting,the simulation results prove that the proposed method is able to predict time series with random perturbation more accurately.For the practical application,the proposed FIS is applied to predicting the time series of ship maneuvering motion.To obtain actual time series data records,the ship maneuvering motion trial is conducted in the Yukun ship of Dalian Maritime University in China.The time series forecasting results show that the FIS constructed with DM concepts can forecast ship maneuvering motion robustly and effectively. 展开更多
关键词 partition robustness forecasting membership noisy perturbation triangular automatically Maritime refining
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