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Found 18 papers, 3 papers with code
RELATE: Generating a linguistically inspired Knowledge Graph for fine-grained emotion classification
These resources are either large, common-sense knowledge graphs (KG) that cover a limited amount of polarities/emotions or they are smaller in size (e. g.: lexicons), which require costly human annotation and cover fine-grained emotions.
A Deep Learning Framework for Wind Turbine Repair Action Prediction Using Alarm Sequences and Long Short Term Memory Algorithms
With an increasing emphasis on driving down the costs of Operations and Maintenance (O&M) in the Offshore Wind (OSW) sector, comes the requirement to explore new methodology and applications of Deep Learning (DL) to the domain.
Scientometric Review of Artificial Intelligence for Operations & Maintenance of Wind Turbines: The Past, Present and Future
Wind energy has emerged as a highly promising source of renewable energy in recent times.
XAI4Wind: A Multimodal Knowledge Graph Database for Explainable Decision Support in Operations & Maintenance of Wind Turbines
Condition-based monitoring (CBM) has been widely utilised in the wind industry for monitoring operational inconsistencies and failures in turbines, with techniques ranging from signal processing and vibration analysis to artificial intelligence (AI) models using Supervisory Control & Acquisition (SCADA) data.
A Deep Learning Approach Towards Prediction of Faults in Wind Turbines
With the rising costs of conventional sources of energy, the world is moving towards sustainable energy sources including wind energy.
Dilated LSTM with attention for Classification of Suicide Notes
In this paper we present a dilated LSTM with attention mechanism for document-level classification of suicide notes, last statements and depressed notes.
