Chủ nhật, 26/07/2026 | 17:20

Using wavelet transform to improve quality classfication for time-series data sequence Abstract: This paper proposes a solution using wavelet transform to extract features from a time-series, the outputs of the pre-processing is input of a neural network in order to classify and predict near future trends of the data. The approach is based on the CWT and DWT of time-series. The result which is tested on real datasets HAR (Human Activity Recognition), shows the improvements in accuracy, reaching 94%. It is an improvement compared to previously reported results for previous systems. Key words:Time-series, wavelet transform, machine learning, deep learning. |
Bộ Công Thương xác định thực hiện Nghị quyết số 57-NQ/TW là nhiệm vụ chính trị quan trọng, thường xuyên và việc triển khai phải đồng bộ, quyết liệt.
24/07/2026