Two-Factor Fuzzy Time Series for Equipment Data Prediction

doi:10.1007/s12204-018-1983-0

Journal of Shanghai Jiao Tong University (Science) ›› 2018, Vol. 23 ›› Issue (5): 684-690.doi: 10.1007/s12204-018-1983-0

Two-Factor Fuzzy Time Series for Equipment Data Prediction

HE Shanhong (何善红), RONG Baizhong (荣百中), QU Meng (瞿勐), WANG Shuangfei (王双飞), LI Huanhuan (李欢欢), WANG Fengyang (王冯阳), WU Jin (吴进)

(Suzhou Nuclear Power Research Institute, Shenzhen 518026, Guangdong, China)

出版日期:2018-10-01 发布日期:2018-10-07
通讯作者: HE Shanhong (何善红) E-mail:heshanhong@cgnpc.com.cn

Two-Factor Fuzzy Time Series for Equipment Data Prediction

HE Shanhong (何善红), RONG Baizhong (荣百中), QU Meng (瞿勐), WANG Shuangfei (王双飞), LI Huanhuan (李欢欢), WANG Fengyang (王冯阳), WU Jin (吴进)

(Suzhou Nuclear Power Research Institute, Shenzhen 518026, Guangdong, China)

Online:2018-10-01 Published:2018-10-07
Contact: HE Shanhong (何善红) E-mail:heshanhong@cgnpc.com.cn

摘要/Abstract

摘要： The data forecasting of plant equipment plays an important role in assurance of the safe and reliable operation of the plant equipment. Thus, it is necessary to improve the accuracy of data forecasting of the equipment. A new two-factor fuzzy time series algorithm is proposed to forecast the data of the plant equipment. This method not only overcomes the limitations of one factor fuzzy time series algorithm, but also overcomes the drawbacks of traditional two-factor fuzzy time series algorithm. The collected data is used in the power plant to conduct experiments, where the metrics is Mean Absolute Percentage Error (MAPE). The results show that this method is superior to the existing two-factor fuzzy time series algorithms, and yields good results in the equipment prediction.

关键词: equipment prediction, fuzzy time series, two-factor fuzzy time series

Abstract: The data forecasting of plant equipment plays an important role in assurance of the safe and reliable operation of the plant equipment. Thus, it is necessary to improve the accuracy of data forecasting of the equipment. A new two-factor fuzzy time series algorithm is proposed to forecast the data of the plant equipment. This method not only overcomes the limitations of one factor fuzzy time series algorithm, but also overcomes the drawbacks of traditional two-factor fuzzy time series algorithm. The collected data is used in the power plant to conduct experiments, where the metrics is Mean Absolute Percentage Error (MAPE). The results show that this method is superior to the existing two-factor fuzzy time series algorithms, and yields good results in the equipment prediction.

Key words: equipment prediction, fuzzy time series, two-factor fuzzy time series

中图分类号:

TP 806

HE Shanhong (何善红), RONG Baizhong (荣百中), QU Meng (瞿勐), WANG Shuangfei (王双飞), LI H. Two-Factor Fuzzy Time Series for Equipment Data Prediction[J]. Journal of Shanghai Jiao Tong University (Science), 2018, 23(5): 684-690.

HE Shanhong (何善红), RONG Baizhong (荣百中), QU Meng (瞿勐), WANG Shuangfei (王双飞), LI Huanhuan (李欢欢), WANG Fengyang (王冯阳), WU Jin (吴进). Two-Factor Fuzzy Time Series for Equipment Data Prediction[J]. Journal of Shanghai Jiao Tong University (Science), 2018, 23(5): 684-690.

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Two-Factor Fuzzy Time Series for Equipment Data Prediction

Two-Factor Fuzzy Time Series for Equipment Data Prediction

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