Virtual sample generation method based on generative adversarial fuzzy neural network

Author:

Cui Canlin,Tang JianORCID,Xia Heng,Qiao Junfei,Yu Wen

Funder

Innovative Research Group Project of the National Natural Science Foundation of China

National Natural Science Foundation of China

Natural Science Foundation of Beijing Municipality

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Reference48 articles.

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2. Pan TY, Chen JL, Zhang TC, Liu S, He SL, Lv HX (2021) Generative adversarial network in mechanical fault diagnosis under small sample: A systematic review on applications and future perspectives. ISA Trans 128(Part B):1–10

3. Yin S, Ding XS, Xie XC, Luo H (2014) A review on basic data-driven approaches for industrial process monitoring. IEEE Trans Ind Electron 61(11):6418–6428

4. Zhu JL, Ge ZQ, Song ZH, Gao FR (2018) Review and big data perspectives on robust data mining approaches for industrial process modeling with outliers and missing data. Annu Rev Control 46:107–133

5. Chen Y, Xu P, Chu Y et al (2017) Short-term electrical load forecasting using the support vector regression (SVR) model to calculate the demand response baseline for office buildings. Appl Energy 195:659–670

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