使用人工智能算法对风速预测中的数据大小变量的研究
M A Ehsan1, Amir Shahirinia1, Nian Zhang1
1Department of Electrical and Computer Engineering, University of the District of Columbia, Washington, DC, USA.
概括
使用人工智能算法预测风速对于可再生能源规划至关重要. 预测风速的最佳人工智能模型取决于可用的数据集的大小.
科学领域:
- 可再生能源系统可再生能源系统
- 人工智能应用程序 人工智能应用程序
- 环境科学 环境科学
背景情况:
- 化石燃料发电有助于全球变暖.
- 可再生能源提供了一个可持续的替代方案,减少工业排放.
- 分散的能源生产提高了能源独立性.
研究的目的:
- 预测风速,以改善风电场的规划和可行性.
- 评估各种人工智能算法的风速预测准确度.
主要方法:
- 采集的气象数据被利用.
- 用十二种不同的人工智能算法来预测风速.
- 基于不同数据集大小的预测准确度来评估模型性能.
主要成果:
- 这项研究比较了12个人工智能算法的性能.
- 在算法中,风速预测的准确性各不相同.
- 风速预测的最佳算法被发现是数据大小依赖的.
结论:
- 准确的风速预测对于有效的风能集成至关重要.
- 人工智能为预测风力等间歇性可再生资源提供了强大的工具.
- 根据数据可用性选择合适的AI模型是成功开发风电场的关键.
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