Results 61 to 70 of about 3,794 (184)

Attention and Geological Knowledge Guided Spectral‐Spatial Networks for Geochemical Anomalies Recognition

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 4, August 2026.
Abstract Achieving both accuracy and interpretability in deep learning models for geochemical anomaly recognition constitutes a significant challenge. To overcome this challenge, this study developed a novel interpretable dual‐branch network combining a spectral attention bidirectional RNN (BiRNN) branch and a spatial attention CNN branch guided with ...
Yihui Xiong, Zhixiang Liang, Zhiyi Chen, Yao Fan, Renguang Zuo   +4 more
wiley   +1 more source

Cryptocurrency Price Prediction Model Using GRU, LSTM and Bi-LSTM Machine Learning Algorithms

Proceedings of the International Conference on Applied Innovations in IT
The rapid rise of cryptocurrencies has indeed created both investment opportunities and forecasting challenges. Accurate predictions of cryptocurrency prices are crucial for traders and financial planners to make informed decisions.
Laila Suwaid Said
doaj   +1 more source

Speech and Language Markers of Bipolar Disorder: Challenges and Opportunities

Bipolar Disorders, Volume 28, Issue 5, August 2026.
ABSTRACT Background Clinicians aspire to predict the emergence of Bipolar Disorder (BD) in a timely manner. To accomplish this, markers reflecting mental states that can be gathered non‐invasively and at large scale are needed. Here, we systematically evaluate evidence relating speech‐based markers to mood states in BD.
Farida Zaher, Jessica Ahrens, Delphine Raucher‐Chéné, Alban Voppel, Lena Palaniyappan   +4 more
wiley   +1 more source

A New Hybrid Deep Learning Method with Neutrosophic Sets for Social Media Sentiment Analysis of the COVID-19 Vaccine [PDF]

Neutrosophic Sets and Systems
The COVID-19 pandemic has launched historic public debates on vaccines, and more significantly, on social media posts regarding vaccines. In this study, we investigate how the public thinks about COVID19 vaccinations using state-of-the-art machine ...
Tasneem Abdelrahman, Mohamed El-Rashidy, Mohamed Marie   +2 more
doaj   +1 more source

Bismuth Single‐Atom Decorated Crystalline/Amorphous Ru/RuO2 Heterojunctions With Abundant Oxygen Vacancies for pH‐Universal Hydrogen Evolution Reaction

Carbon Neutralization, Volume 5, Issue 4, July 2026.
We designed Bi single‐atom modified heterojunctions composed of crystalline Ru and amorphous RuO2 for the full‐pH hydrogen evolution reaction. Bi single‐atom doping effectively suppresses the overoxidation of Ru active sites, optimizes the electronic structure, and triggers pronounced interfacial charge redistribution, thereby significantly boosting ...
Meng Jin, Xuanlin Kuang, Longyu Qiu, Fangxu Lin, Yuqing Liu, Xiaoping Hu, Jun Zhang, Yin Liu, Juan Liu, Chuan Tan, Menggang Li, Zhigang Zou, Shi‐Yu Lu   +12 more
wiley   +1 more source

Gravitational Search Algorithm Enhanced Bidirectional LSTM With Graph Neural Networks: A Hybrid Approach to Groundwater Quality Prediction

Engineering Reports, Volume 8, Issue 7, July 2026.
Gravitational search algorithm enhanced bidirectional LSTM with graph neural networks. ABSTRACT Water quality is a crucial factor in sustainable development. In recent years, water contamination induced by urban development, industrialization, and human activities has been a serious concern for all living species.
C. Subashini, Suseela Sellamuthu
wiley   +1 more source

Forecasting Shifts in Europe's Renewable and Fossil Fuel Markets Using Deep Learning Methods

Energy Science & Engineering
Accurate forecasts of renewable and nonrenewable energy output are essential for meeting global energy needs and resolving environmental issues. Energy sources like the sun and wind are variable, making forecasting difficult.
Yonghong Liu, Muhammad S. Saleem, Javed Rashid, Sajjad Ahmad, Muhammad Faheem   +4 more
doaj   +1 more source

CNN-GRU for Drowsiness Detection from Electrocardiogram Signal

ComTech
Drowsiness is a problem that needs to be addressed to improve road safety. To minimize this safety issue, driving-monitoring systems have been implemented in current car models, and electrocardiography (ECG) is one of the most commonly used driving ...
Setiawan Hendratno, Nico Surantha
doaj   +1 more source

A Bi-GRU-DSA-based social network rumor detection approach

Open Computer Science
AbstractIn the rumor detection based on crowd intelligence, the crowd behavior is constructed as a graph model or probability mode. The detection of rumors is achieved through the collaborative utilization of data and knowledge. Aiming at the problems of insufficient feature extraction ability and data redundancy of current rumor detection methods ...
Huang, Xiang, Liu, Yan
openaire   +2 more sources

Research on network traffic prediction based on Bi-GRU model

Dianzi Jishu Yingyong, 2022
At present, there are some problems such as lag and low prediction accuracy when using gated recurrent units(GRU) neural network to predict traffic. This paper proposes an improved GRU model for traffic prediction. Firstly, based on GRU neural network, a network model integrating Bi-GRU neural network and artificial neural network is proposed, which ...
Xu Haibing, Guo Jiuming
openaire   +1 more source