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Missing interpolation model for wind power data based on the improved CEEMDAN method and generative adversarial interpolation network 被引量:3
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作者 Lingyun Zhao zhuoyu wang +4 位作者 Tingxi Chen Shuang Lv Chuan Yuan Xiaodong Shen Youbo Liu 《Global Energy Interconnection》 EI CSCD 2023年第5期517-529,共13页
Randomness and fluctuations in wind power output may cause changes in important parameters(e.g.,grid frequency and voltage),which in turn affect the stable operation of a power system.However,owing to external factors... Randomness and fluctuations in wind power output may cause changes in important parameters(e.g.,grid frequency and voltage),which in turn affect the stable operation of a power system.However,owing to external factors(such as weather),there are often various anomalies in wind power data,such as missing numerical values and unreasonable data.This significantly affects the accuracy of wind power generation predictions and operational decisions.Therefore,developing and applying reliable wind power interpolation methods is important for promoting the sustainable development of the wind power industry.In this study,the causes of abnormal data in wind power generation were first analyzed from a practical perspective.Second,an improved complete ensemble empirical mode decomposition with adaptive noise(ICEEMDAN)method with a generative adversarial interpolation network(GAIN)network was proposed to preprocess wind power generation and interpolate missing wind power generation sub-components.Finally,a complete wind power generation time series was reconstructed.Compared to traditional methods,the proposed ICEEMDAN-GAIN combination interpolation model has a higher interpolation accuracy and can effectively reduce the error impact caused by wind power generation sequence fluctuations. 展开更多
关键词 Wind power data repair Complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN) Generative adversarial interpolation network(GAIN)
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Preliminary Study on Effects of Anthraquinone Extract of Polygonum cuspidatum on KHV
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作者 zhuoyu wang Ming CHEN +4 位作者 Bingkun YANG Changyou LIU Chanjuan CHEN Lihe FAN Yongjun wang 《Asian Agricultural Research》 2022年第1期72-76,共5页
[Objectives]To study the toxic effect and antiviral activity of anthraquinone extract of Polygonum cuspidatum on infection of Koi herpes virus(KHV).[Methods]The MTT method and CPE microscopy were used to detect the co... [Objectives]To study the toxic effect and antiviral activity of anthraquinone extract of Polygonum cuspidatum on infection of Koi herpes virus(KHV).[Methods]The MTT method and CPE microscopy were used to detect the common carp brain(CCB)cytotoxicity of the P.cuspidatum anthraquinone extract in 48 h.Eight groups of different concentrations of the P.cuspidatum anthraquinone extract 1.96,3.91,7.28,15.63,31.25,62.5,125,250μg/mL experimental groups and a control group without drug effect were set up.After determining the maximum non-toxic range of the P.cuspidatum anthraquinone extract,the viral replication inhibition test was carried out.[Results]The concentration of the P.cuspidatum anthraquinone extract 31.25μg/mL was recognized as the maximum non-toxic concentration.The survival rate of CCB cells was higher than 80%,and the toxic dose(CC50)of the drug for 50%cell death was(72.67±2.12)μg/mL.The maximum inhibition rate of the P.cuspidatum anthraquinone extract was 78.63%±5.47%at a concentration of 31.25μg/mL,and the 50%effective drug dose(IC50)for inhibiting the virus was(13.67±0.47)μg/mL,and the therapeutic index(TI)was 5.48±0.49.In the direct virus killing test,the highest virus inhibition rate was 32.21%.[Conclusions]Under the experimental conditions,it can be concluded that the P.cuspidatum anthraquinone extract has high anti-KHV activity,and at the same time.It is expected to lay a theoretical foundation for the research of P.cuspidatum anthraquinone extract against KHV. 展开更多
关键词 Polygonum cuspidatum Koi herpes virus(KHV) Antiviral effect
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