Spatio-temporal graph neural networks for multi-site PV power forecasting
J Simeunović, B Schubnel, PJ Alet… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Accurate forecasting of solar power generation with fine temporal and spatial resolution is
vital for the operation of the power grid. However, state-of-the-art approaches that combine …
vital for the operation of the power grid. However, state-of-the-art approaches that combine …
Multi-label emotion classification based on adversarial multi-task learning
N Lin, S Fu, X Lin, L Wang - Information Processing & Management, 2022 - Elsevier
In this paper, we focus on the task of multi-label emotion classification and aim to tackle two
problems of this task. First, few studies try to exploit the correlation among different emotions …
problems of this task. First, few studies try to exploit the correlation among different emotions …
Vision-based activity classification of excavators by bidirectional LSTM
Advancements in deep learning and vision-based activity recognition development have
significantly improved the safety, continuous monitoring, productivity, and cost of the …
significantly improved the safety, continuous monitoring, productivity, and cost of the …
C-BDCLSTM: A false emotion recognition model in micro blogs combined Char-CNN with bidirectional dilated convolutional LSTM
Z Hou, Y Du, W Li, J Hu, H Li, X Li, X Chen - Applied Soft Computing, 2022 - Elsevier
In recent years, researchers are enthusiastic about the field of sentiment computing. They
pay attention to normal emotion recognition, but little to abnormal emotion recognition. In …
pay attention to normal emotion recognition, but little to abnormal emotion recognition. In …
Classifying suicide-related content and emotions on Twitter using Graph Convolutional Neural Networks
Recent work in Natural Language Processing has increasingly focused on detecting suicidal
intent in textual data, where the main aim is to detect expressions in a binary setting …
intent in textual data, where the main aim is to detect expressions in a binary setting …
Fine-Grained Sentiment Analysis of Cross-Domain Chinese E-commerce Texts Based on SKEP_Gram-CDNN
Y Zhang, C Zhu, Y Xie - IEEE Access, 2023 - ieeexplore.ieee.org
This study aims to use pre-trained models and an improved DPCNN model to extract useful
information for sentiment analysis in an e-commerce dataset by combining a general …
information for sentiment analysis in an e-commerce dataset by combining a general …
Positional multi-length and mutual-attention network for epileptic seizure classification
G Zhang, A Zhang, H Liu, J Luo, J Chen - Frontiers in Computational …, 2024 - frontiersin.org
The automatic classification of epilepsy electroencephalogram (EEG) signals plays a crucial
role in diagnosing neurological diseases. Although promising results have been achieved …
role in diagnosing neurological diseases. Although promising results have been achieved …
Understanding Slang with LLMs: Modelling Cross-Cultural Nuances through Paraphrasing
In the realm of social media discourse, the integration of slang enriches communication,
reflecting the sociocultural identities of users. This study investigates the capability of large …
reflecting the sociocultural identities of users. This study investigates the capability of large …
Technical domain identification using word2vec and BiLSTM
Coarse-grained and Fine-grained classification tasks are mostly based on sentiment or
basic emotion analysis. Now, switching from emotion and sentiment analysis to another …
basic emotion analysis. Now, switching from emotion and sentiment analysis to another …
Network time series forecasting in photovoltaics power production
J Simeunovic - 2024 - infoscience.epfl.ch
Accurate forecasting of photovoltaic (PV) power production is crucial for the integration of
more renewable energy sources into the power grid. PV power production is highly …
more renewable energy sources into the power grid. PV power production is highly …