Search Results - subject:"short term memory"

A clinical named entity recognition model using pretrained word embedding and deep neural networks

Dash, Adyasha; Darshana, Subhashree; Yadav, Devendra K.; … - 2024

Clinical Named Entity Recognition (NER) within Electronic Medical Records (EMRs) has seen substantial research attention. Since much clinical information resides in unstructured text, NER technology is pivotal in extracting vital patient data from such sources. The ubiquity of EMRs has fueled...

Persistent link: https://www.econbiz.de/10015101649

Coupling LSTM neural networks and state-space models through analytically tractable inference

Vuong, Van-Dai; Nguyen, Luong-Ha; Goulet, James-A. - In: International journal of forecasting 41 (2025) 1, pp. 128-140

Persistent link: https://www.econbiz.de/10015440244

Forecasting federal fund rates with AI : LSTM, GRU, and large language model approaches

Chan-Lau, Jorge A.; Quach, Toan Long; Shi, Rui - 2025

Persistent link: https://www.econbiz.de/10015453621

Yield curve extrapolation with machine learning

Akiyama, Shinobu; Matsuyama, Naoki - In: ASTIN bulletin : the journal of the International … 55 (2025) 1, pp. 76-96

extrapolation method using machine learning. Using the long short-term memory architecture, we achieve purely data-driven yield …

Persistent link: https://www.econbiz.de/10015450022

Short-term hourly hydropower prediction : evaluating LSTM and MILP-based methods

Villeneuve, Yoan; Séguin, Sara; Chehri, Abdellah; … - 2025

Persistent link: https://www.econbiz.de/10015404003

Using machine learning to identify hidden constraints in vehicle routing problems

Konovalenko, Anna; Hvattum, Lars Magnus; Msakni, … - In: Computers & operations research : an international journal 179 (2025), pp. 1-10

Persistent link: https://www.econbiz.de/10015338572

Comparative study of forecasting methods to predict the energy demand for the market of Colombia

Vargas-Forero, Victor Manuel; Manotas-Duque, Diego Fernando - In: International Journal of Energy Economics and Policy : IJEEP 15 (2025) 1, pp. 65-76

Persistent link: https://www.econbiz.de/10015333827

Capturing complex electricity load patterns : a hybrid deep learning approach with proposed external-convolution attention

Zare, Mohammad Sadegh; Nikoo, Mohammad Reza; Chen, Mingjie - In: Energy strategy reviews 57 (2025), pp. 1-15

Convolutional Neural Network, Temporal Convolutional Network, and Bidirectional Long Short-Term Memory with a proposed attention …

Persistent link: https://www.econbiz.de/10015432128

A long short-term memory enhanced realized conditional heteroskedasticity model

Liu, Chen; Wang, Chao; Minh-Ngoc Tran; Kohn, Robert - In: Economic modelling 142 (2025), pp. 1-10

Persistent link: https://www.econbiz.de/10015192384

Bayesian-optimized ensemble deep learning models for demand forecasting in the volatile situations : a case study of grocery demand during Covid-19 outbreaks

Al Theeb, Nader; Smadi, Hazem; Al-Qaydeh, Naser - In: Journal of industrial engineering and management : JIEM 18 (2025) 1, pp. 193-213

.Design/methodology/approach: An ensemble model that based on combining Bayesian-optimized Long Short-Term Memory (BO-LSTM) and Gated Recurrent Unit …

Persistent link: https://www.econbiz.de/10015414985