Data mining with wavelet analysis are used to create a combined renewable energy prediction model

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作者

Seemant Tiwari¹

1. Dept. of Electrical Engineering, Southern Taiwan University of Science and Technology,Taiwan

会议/活动

Asian Conference on Machine Learning, 2021, November 2021 (Singapore, Singapore)

海报摘要

In large distribution networks and distributed energy, wind energy is critical. Grid power balance relies heavily on accurate wind farm predictions. For effectively extraction characteristics using wind time series analysis, this poster offers a time - series data fuzzy c-means grouping technique and also a clusters selection algorithm. Clustering analysis is an effective approach for data processing which is often utilised. Cluster analysis is used to partition large datasets in subgroups based on similarity as differences. A wavelet decomposition is being used to split down wind energy output and to provide the MLNARx with more appropriate inputs. A comparison with well-known estimation methods reveals that the suggested estimation method outperforms them.

关键词

Prediction, Wavelet, Neural network, Clustering

研究领域

Electrical Engineering

参考文献

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基金

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补充材料

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附加信息

利益冲突

No competing interests were disclosed.

数据可用性声明

Data sharing not applicable to this poster as no datasets were generated or analyzed during the current study.

知识共享许可协议

Copyright © 2023 Tiwari. This is an open access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.