Results 261 to 270 of about 3,183,655 (317)

Nonlinear Dynamic Soft Sensor Modeling With Supervised Long Short-Term Memory Network

IEEE Transactions on Industrial Informatics, 2020
Soft sensor has been extensively utilized in industrial processes for prediction of key quality variables. To build an accurate virtual sensor model, it is very significant to model the dynamic and nonlinear behaviors of process sequential data properly.
Xiaofeng Yuan, Lin Li, Yalin Wang
semanticscholar   +1 more source

Video Summarization with Long Short-Term Memory

European Conference on Computer Vision, 2016
We propose a novel supervised learning technique for summarizing videos by automatically selecting keyframes or key subshots. Casting the problem as a structured prediction problem on sequential data, our main idea is to use Long Short-Term Memory (LSTM),
Ke Zhang, Wei-Lun Chao, Fei Sha, K. Grauman   +3 more
semanticscholar   +1 more source

Short-Term Memory

2013
According to the Atkinson and Shiffrin model, information is held in STM by continually rehearsing it, and without rehearsal it will be almost immediately forgotten. The LTM is seen as a more passive store of information which is available for retrieval but not kept in an activated form.
Laudan B. Jahromi, Crystal I. Bryce
openaire   +2 more sources

Long Short-Term Memory Recurrent Neural Network for Remaining Useful Life Prediction of Lithium-Ion Batteries

IEEE Transactions on Vehicular Technology, 2018
Remaining useful life (RUL) prediction of lithium-ion batteries can assess the battery reliability to determine the advent of failure and mitigate battery risk. The existing RUL prediction techniques for lithium-ion batteries are inefficient for learning
Yongzhi Zhang, R. Xiong, Hongwen He, M. Pecht   +3 more
semanticscholar   +1 more source

Long Short-Term Memory Networks for Accurate State-of-Charge Estimation of Li-ion Batteries

IEEE transactions on industrial electronics (1982. Print), 2018
State of charge (SOC) estimation is critical to the safe and reliable operation of Li-ion battery packs, which nowadays are becoming increasingly used in electric vehicles (EVs), Hybrid EVs, unmanned aerial vehicles, and smart grid systems.
Ephrem Chemali, P. Kollmeyer, Matthias Preindl, R. Ahmed, A. Emadi   +4 more
semanticscholar   +1 more source

A hybrid model for spatiotemporal forecasting of PM2.5 based on graph convolutional neural network and long short-term memory.

Science of the Total Environment, 2019
Increasing availability of data related to air quality from ground monitoring stations has provided the chance for data mining researchers to propose sophisticated models for predicting the concentrations of different air pollutants.
Yanli Qi, Qi Li, Hamed Karimian, Dingzhong Liu   +3 more
semanticscholar   +1 more source

Developing a Long Short-Term Memory (LSTM) based model for predicting water table depth in agricultural areas

Journal of Hydrology, 2018
Predicting water table depth over the long-term in agricultural areas presents great challenges because these areas have complex and heterogeneous hydrogeological characteristics, boundary conditions, and human activities; also, nonlinear interactions ...
Jianfeng Zhang, Yan Zhu, Xiaoping Zhang, M. Ye, Jin-zhong Yang   +4 more
semanticscholar   +1 more source

Fault diagnosis of wind turbine based on Long Short-term memory networks

Renewable Energy, 2019
Time-series data is widely adopted in condition monitoring and fault diagnosis of wind turbines as well as other energy systems, where long-term dependency is essential to form the classifiable features.
Jinhao Lei, Chao Liu, D. Jiang
semanticscholar   +1 more source

A Long Short-Term Memory deep learning network for the prediction of epileptic seizures using EEG signals

Comput. Biol. Medicine, 2018
The electroencephalogram (EEG) is the most prominent means to study epilepsy and capture changes in electrical brain activity that could declare an imminent seizure. In this work, Long Short-Term Memory (LSTM) networks are introduced in epileptic seizure
Kostas M. Tsiouris, V. Pezoulas, M. Zervakis, S. Konitsiotis, D. Koutsouris, D. Fotiadis   +5 more
semanticscholar   +1 more source

Short-Term Memory

2015
Digit span is included in the most widely used intelligence test, the Wechsler Adult Intelligence Scale. The digit span test is typically referred to as reflecting short-term memory (STM), and the more complex task as working memory span. The memory system or systems responsible for STM do however form part of the working memory system.
B.J. Dungan, E.K. Vogel
openaire   +2 more sources