Devdiscourse

AI-driven rainfall forecasting shows major gains in predicting flood-triggering storms

Rainfall prediction has advanced rapidly with the adoption of machine learning, but most models remain optimized for overall ...
EurekAlert!

LSTM resolves the long-standing trade-off between sensitivity and measurement range

Researchers in China propose and experimentally demonstrates a novel, deep learning-driven spectral recognition strategy, which achieves a wide dynamic measurement range beyond the free spectral range ...
eLife

High-Fidelity Neural Speech Reconstruction through an Efficient Acoustic-Linguistic Dual-Pathway Framework

This study presents a valuable advance in reconstructing naturalistic speech from intracranial ECoG data using a dual-pathway model. The evidence supporting the claims of the authors is solid, ...
GitHub

Tanishk190/Eurusd-lstm-predictor

A machine learning web application that predicts the next day's closing price for the EUR/USD currency pair using historical data and LSTM neural networks. ML-Project/ ├── app.py # Flask web ...
24/7 Wall St

300 Banks Use RippleNet, But XRP Transaction Volume Is Falling: What Gives?

XRP’s transaction volume continues declining even as RippleNet expands to over 300 banking partners. Banks use RippleNet’s infrastructure without requiring XRP because the token remains optional for ...
Frontiers

Multi-field numerical model and LSTM-based neural networks for thermal field predictions of concrete-filled steel tubes

1 Construction Branch of State Gird Jiangsu Electric Power Co. Ltd, Nanjing, China 2 Civil Engineering School, Southeast University, Nanjing, China Concrete-filled steel tube (CFST) columns are widely ...
IEEE

LSTM Neural Networks Anomaly Detection for Biotic and Abiotic Early Stress Detection on Tomato Plants

Abstract: This study explores time series anomaly detection using a long short-term memory (LSTM) neural network to identify abnormal plant conditions—both biotic and abiotic—by analyzing a stem ...
Frontiers

Intelligent forecasting model for aquatic production based on artificial neural network

Aquaculture is recognized as a critical component of global food security and economic development, playing an indispensable role in meeting nutritional needs and supporting livelihoods worldwide.
IEEE

Long Short-Term Memory Neural Network Combined With a Hybrid-Modular Clockwork Structure for Transient Modeling of Nonlinear Circuits

Abstract: This paper presents a novel macromodeling method and neural network structure called Clockwork Long Short-Term Memory (CWLSTM), tailored for high-speed nonlinear circuits. The proposed ...