Results 81 to 90 of about 35,156 (275)

TAMNet: Temporal and adaptive‐frequency network with MixStyle for cross‐region oil and fluid production forecasting

Deep Underground Science and Engineering, EarlyView.
This paper presents temporal and adaptive‐frequency network with MixStyle (TAMNet), a deep time‐series modeling framework for accurate and robust multi‐well oil productivity forecasting. TAMNet integrates transformer and long short‐term memory architectures to capture both short‐ and long‐term temporal dependencies, enhanced by a temporal gate unit ...
Chunxi Yang, Leifeng Meng, Qinghu Fan, Ziang Guo, Ting Bao, Pingdong Zhong, Fulin Luo   +6 more
wiley   +1 more source

Classification of User Expressions on Social Media Using LSTM and GRU Models

Jurnal Sisfokom
Social media serves as a platform for sharing information. Through social media, users can interact with others and express their feelings and emotions. Therefore, emotion analysis plays a crucial role in understanding users' conditions regarding various
I Gede Putra Mas Yusadara, I Gusti Ayu Desi Saryanti   +1 more
doaj   +3 more sources

The genome sequence of the common crane, Grus grus (Linnaeus, 1758)

Wellcome Open Research
We present a genome assembly from a male specimen of Grus grus (common crane; Chordata; Aves; Gruiformes; Gruidae). The assembly contains two haplotypes with total lengths of 1,352.26 megabases and 1,291.08 megabases.
O’Brien, Michelle F., Lopez Colom, Rosa   +1 more
openaire   +2 more sources

Second observation of Common Crane Grus grus in Senegal

Bulletin of the African Bird Club, 2013
(Uploaded by Plazi from the Biodiversity Heritage Library) No abstract provided.
Volker Salewski, Troels Eske Ortvad, Kasper Thorup   +2 more
openaire   +2 more sources

Artificial intelligence for adaptive neuromodulation in drug‐resistant epilepsy

Epilepsia, EarlyView.
Abstract Drug‐resistant epilepsy (DRE) affects nearly one third of people with epilepsy and is associated with substantial cognitive, psychiatric, and mortality burdens. For patients who are not candidates for resection or laser interstitial thermal therapy, neuromodulation therapies such as vagus nerve stimulation, deep brain stimulation, and ...
Amir Hossein Daraie, Arianna Damiani, Mahsa Khoshkhou, Luis A. Sanchez, Rachel J. Smith, Shruti H. Agashe, Jorge A. Gonzalez‐Martinez, Jennifer Hopp, Adam S. Charles, Sridevi V. Sarma, Joon‐Yi Kang   +10 more
wiley   +1 more source

AI‐based localization of the epileptogenic zone using intracranial EEG

Epilepsia Open, EarlyView.
Abstract Artificial intelligence (AI) is rapidly transforming our lives. Machine learning (ML) enables computers to learn from data and make decisions without explicit instructions. Deep learning (DL), a subset of ML, uses multiple layers of neural networks to recognize complex patterns in large datasets through end‐to‐end learning.
Atsuro Daida, Yipeng Zhang, Sotaro Kanai, Richard Staba, Vwani Roychowdhury, Hiroki Nariai   +5 more
wiley   +1 more source

Machine Learning for Energy Forecasting in Smart Homes – A Comparative Model Study : An Evaluation of LSTM, GRU, Random Forest, and ARIMA [PDF]

I takt med att energiförbrukningen i hushåll ökar och smarta hem blir allt vanligare, uppstår ett växande behov av intelligenta system som kan optimeraenergianvändningen.
Hadziabdic, Haris, Khelifa, Mohamed
core   +2 more sources

GRU-LSTM Model Based on the SSA for Short-Term Traffic Flow Prediction [PDF]

The transportation department relies on accurate traffic forecasting for effective decision-making. However, determining relevant parameters for existing traffic flow prediction models poses challenges. To address this issue, this study proposes a hybrid
Ma, Changxi, Zhao, Yongpeng, Huang, Xiaoyu, Wang, Tao, Du, Bo   +4 more
core   +2 more sources

Feasibility of Wind‐Powered Green Hydrogen Production via a Hybrid Graph Neural Network‐Transformer Forecasting Model

Energy Science &Engineering, EarlyView.
ABSTRACT Accurate long‐term wind speed forecasting is pivotal for the strategic planning of renewable energy infrastructure, particularly for assessing the techno‐economic feasibility of wind‐powered green hydrogen facilities. However, capturing the complex spatiotemporal dependencies in climate data remains a significant challenge. This study proposes
Iman Baghaei, Mojtaba Mirhosseini, Alireza Zahedi   +2 more
wiley   +1 more source

Detecting Language Anxiety in Indonesian Students: Deep Learning and Traditional Classification Methods for English Learning Anxiety

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Mastery of the English language represents a fundamental determinant of professional achievement, particularly for individuals seeking to develop their careers and participate in international contexts.
Kemas Muslim Lhaksmana, Muhammad Sya’bani Falif, Iis Kurnia Nurhayati, Muhammad Yudhi Rezaldi, Esa Prakasa, Rickman Roedavan   +5 more
doaj   +1 more source