Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Li Shengzhu"'
Publikováno v:
SHS Web of Conferences, Vol 169, p 01043 (2023)
The digital sharing of agricultural scientific and technological resources is the key to promoting agricultural scientific and technological innovation. Explore the strategic mechanism for the digital sharing of agricultural scientific and technologi
Externí odkaz:
https://doaj.org/article/35c29e22257a42dbbd062221a7d82e3b
Autor:
Lin, Yongchuan, Ma, Jiyang, Lai, Debin, Zhang, Jingru, Li, Weizhu, Li, Shengzhu, He, Shengjian
Publikováno v:
In Heliyon November 2022 8(11)
Publikováno v:
Journal of Cardiovascular Translational Research; Oct2024, Vol. 17 Issue 5, p1155-1171, 17p
Publikováno v:
Journal of Physics: Conference Series; 2024, Vol. 2741 Issue 1, p1-6, 6p
Autor:
Li, Shengzhu1 (AUTHOR), Jiang, Fan1 (AUTHOR) 1442468224@qq.com
Publikováno v:
PLoS ONE. 7/21/2022, Vol. 17 Issue 7, p1-18. 18p.
Autor:
Liu, Yingkai, Li, Shengzhu
Publikováno v:
Proceedings of SPIE; March 2024, Vol. 13075 Issue: 1 p130750N-130750N-10, 12944261p
Akademický článek
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Publikováno v:
2017 29th Chinese Control And Decision Conference (CCDC).
According to analyze the output characteristics of photovoltaic (PV) array and the advantages and disadvantages of the traditional maximum power point tracking (MPPT) method, an improved increment conductance (INC) method was proposed. Using MATLAB/S
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::03dabc718c3a6e8e1a9039b6d347f176
https://doi.org/10.1109/ccdc.2017.7978907
https://doi.org/10.1109/ccdc.2017.7978907
Publikováno v:
2016 Chinese Control and Decision Conference (CCDC).
In this document, a BP neural network based PID control is designed considering the characteristics of solar power generation based on profound research on BP neural network control technique. In addition, computerized control program has been develo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cb3cb7fec8e6a362eca4c4cb7a92b890
https://doi.org/10.1109/ccdc.2016.7531037
https://doi.org/10.1109/ccdc.2016.7531037
Publikováno v:
Physics Procedia. 24:626-632
The load forecast level in power system is a important symbol to measure operations and management of power system. This paper summarized the research conditions of the short-term load forecasting using artificial neural network method, and analyzed
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dd134e6768fc8bb479ab5aa0430515fa