Results 291 to 300 of about 13,220,426 (366)

News Recommendation with Attention Mechanism

open access: yesarXiv.org
This paper explores the area of news recommendation, a key component of online information sharing. Initially, we provide a clear introduction to news recommendation, defining the core problem and summarizing current methods and notable recent algorithms.
Tianrui Liu   +4 more
semanticscholar   +4 more sources

A Deep Reinforcement Learning Framework Based on an Attention Mechanism and Disjunctive Graph Embedding for the Job-Shop Scheduling Problem

IEEE Transactions on Industrial Informatics, 2023
The job-shop scheduling problem (JSSP) is a classical NP-hard combinatorial optimization problem, and the operating efficiency of manufacturing system is affected directly by the quality of its scheduling scheme.
R. Chen, Wenxin Li, Hongbin Yang
semanticscholar   +1 more source

Integrated Generative Model for Industrial Anomaly Detection via Bidirectional LSTM and Attention Mechanism

IEEE Transactions on Industrial Informatics, 2023
For emerging industrial Internet of Things (IIoT), intelligent anomaly detection is a key step to build smart industry. Especially, explosive time-series data pose enormous challenges to the information mining and processing for modern industry.
Fanhui Kong   +4 more
semanticscholar   +1 more source

Remaining Useful Life Prediction for Lithium-Ion Batteries With a Hybrid Model Based on TCN-GRU-DNN and Dual Attention Mechanism

IEEE Transactions on Transportation Electrification, 2023
The instability of lithium-ion batteries may result in system operation failure and cause safety accidents, thus predicting the remaining useful life (RUL) accurately is helpful for reducing the risk of battery failure and extending its useful life.
Lei Li   +5 more
semanticscholar   +1 more source

A Self-Interpretable Soft Sensor Based on Deep Learning and Multiple Attention Mechanism: From Data Selection to Sensor Modeling

IEEE Transactions on Industrial Informatics, 2023
For deep learning-based soft sensors, the lack of interpretability and the consequent unreliability has become one of the most important problems. In this article, a neural network scheme called the deep multiple attention soft sensor (DMASS), which ...
Runyuan Guo   +4 more
semanticscholar   +1 more source

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