Approaches and applications of early classification of time series: A review
Early classification of time series has been extensively studied for minimizing class
prediction delay in time-sensitive applications such as medical diagnostic and industrial …
prediction delay in time-sensitive applications such as medical diagnostic and industrial …
Multivariate LSTM-FCNs for time series classification
Over the past decade, multivariate time series classification has received great attention. We
propose transforming the existing univariate time series classification models, the Long …
propose transforming the existing univariate time series classification models, the Long …
Insights into LSTM fully convolutional networks for time series classification
Long short-term memory fully convolutional neural networks (LSTM-FCNs) and Attention
LSTM-FCN (ALSTM-FCN) have shown to achieve the state-of-the-art performance on the …
LSTM-FCN (ALSTM-FCN) have shown to achieve the state-of-the-art performance on the …
[PDF][PDF] 基于联合时序场景和源网荷协同的分布式光伏与储能优化配置
李勇， 姚天宇， 乔学博， 肖娟霞… - TRANSACTIONS OF …, 2022 - dgjsxb.ces-transaction.com
摘要主动配电网可通过协同调度灵活性资源促进分布式光伏(DPV) 电量消纳,
为此提出基于联合时序场景和源-网-荷协同的DPV 与储能系统(ESS) 联合优化配置方法 …
为此提出基于联合时序场景和源-网-荷协同的DPV 与储能系统(ESS) 联合优化配置方法 …
Adversarial attacks on time series
Time series classification models have been garnering significant importance in the
research community. However, not much research has been done on generating adversarial …
research community. However, not much research has been done on generating adversarial …
A fast and accurate similarity measure for long time series classification based on local extrema and dynamic time warping
A Lahreche, B Boucheham - Expert Systems with Applications, 2021 - Elsevier
The problem of similarity measures is a major area of interest within the field of time series
classification (TSC). With the ubiquitous of long time series and the increasing demand for …
classification (TSC). With the ubiquitous of long time series and the increasing demand for …
Time series classification: Nearest neighbor versus deep learning models
W Jiang - SN Applied Sciences, 2020 - Springer
Time series classification has been an important and challenging research task. In different
domains, time series show different patterns, which makes it difficult to design a global …
domains, time series show different patterns, which makes it difficult to design a global …
Generating adversarial samples on multivariate time series using variational autoencoders
Classification models for multivariate time series have drawn the interest of many
researchers to the field with the objective of developing accurate and efficient models …
researchers to the field with the objective of developing accurate and efficient models …
TCRAN: Multivariate time series classification using residual channel attention networks with time correction
H Zhu, J Zhang, H Cui, K Wang, Q Tang - Applied Soft Computing, 2022 - Elsevier
Currently, the most popular and effective approach to solve multivariate time series
classification (MTSC) tasks is based on deep learning technology. However, the existing …
classification (MTSC) tasks is based on deep learning technology. However, the existing …
Arm motion classification using time-series analysis of the spectrogram frequency envelopes
Z Zeng, MG Amin, T Shan - Remote Sensing, 2020 - mdpi.com
Hand and arm gesture recognition using radio frequency (RF) sensing modality proves
valuable in man–machine interfaces and smart environments. In this paper, we use the time …
valuable in man–machine interfaces and smart environments. In this paper, we use the time …