• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Environmental Research, Engineering and Management >New Hybrid Method Proposal for Wind Speed Prediction: a Case Study of Lüleburgaz
【24h】

New Hybrid Method Proposal for Wind Speed Prediction: a Case Study of Lüleburgaz

机译：风速预测的新混合方法建议：以吕勒堡兹为例

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

This study proposes a hybrid prediction method where Back Propagation Artificial Neural Network (BP-ANN) and Adaptive-Network Based Fuzzy Inference System (ANFIS) Cascade model are used together to predict the wind speed. At the initial stage, to increase the accuracy of prediction, an additional ANFIS layer is used which is driven with outputs acquired from BP-ANN. Thus, a Sugeno type ANFIS model is used for future prediction and prediction capability of a conventional BP-ANN algorithm is increased. At the second stage, BP-ANN outputs and cascade model outputs are compared to the measured value and a selection criteria algorithm is developed that accepts the output very close to the real value. The proposed model generates a prediction output based on a hybrid operation of the two systems unlike the other study in literature. The proposed model is tested with the data taken from the sample station and the results are compared to real calculation values with regard to various statistical error parameters. Results of the study have shown that the hybrid model generates the closest prediction results to the real values compared to the other models. This flexible algorithm developed to predict the wind speed can be also used in other fields in future research.
机译：本研究提出了一种混合预测方法，其中将反向传播人工神经网络（BP-ANN）和基于自适应网络的模糊推理系统（ANFIS）级联模型一起用于预测风速。在初始阶段，为了提高预测的准确性，使用了附加的ANFIS层，该层由从BP-ANN获取的输出驱动。因此，将Sugeno型ANFIS模型用于将来的预测，并且增加了常规BP-ANN算法的预测能力。在第二阶段，将BP-ANN输出和级联模型输出与测量值进行比较，并开发出一种选择标准算法，该算法接受非常接近实际值的输出。与文献中的其他研究不同，所提出的模型基于两个系统的混合操作生成预测输出。利用从采样站获取的数据对提出的模型进行测试，并将结果与​​针对各种统计误差参数的实际计算值进行比较。研究结果表明，与其他模型相比，混合模型生成的预测结​​果与实际值最接近。这种用于预测风速的灵活算法也可以在未来的研究中用于其他领域。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号