问题 |
E3S网页汇编
卷积218,2020
2020年能源环境科学工程国际专题讨论会 |
|
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文章号 | 04023 | |
页数 | 5 | |
段内 | 环境变化监控和城市保护规划 | |
多尔市 | https://doi.org/10.1051/e3sconf/202021804023 | |
在线发布 | 2020年12月11日 |
基于支持向量机的天气分类模式识别研究
一号台北河北经济研究所
2STATE网格经济研究所中国北京
a/对应作者 :523405800@qq.com
weather is the most important factor affecting the photovoltaic power generation.In this paper, the irradiance data of a photovoltaic power station in crodora in 2020 are collected, and the daily out of ground irradiance and the measured irradiance curve of that day are compared and observed, then the weather of that year is classified by human work, and then the daily irradiance data records are counted for the relevant indicators, with the maximum third order Based on the attributes of difference value, discrete difference and normalized variance, it is unified with the classified weather type.Then, the SVM prediction model of weather category is established based on radial basis function, and the optimal model parameters are determined by cross validation, so that a large number of historical date weather categories can be classified and predicted.This is obviously different from the traditional prediction method based on linear statistical theory, and the results show that it has a good effect.
必威西汉姆赞助作者版由EDPScience发布,2020
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