When AI composes Arirang — and reaches for Chinese and Japanese instruments

"At the end of this exhausting day, even pausing to catch your breath is a kind of living ..." (from "The Miracle That Is You ...
IEEE

Classification of Focal and Non-Focal Epileptic Patients Using Single Channel EEG and Long Short-Term Memory Learning System

Abstract: The process of inspecting electroencephalography (EEG) signals of patients with epilepsy to distinguish between focal and non-focal seizure source is a crucial step prior to surgical ...
Frontiers

An interpretable building air conditioning load forecasting framework using SSA-optimized Bi-LSTM and SHAP analysis

Short-term air conditioning load forecasting in industrial buildings plays a key role in energy management and carbon neutrality efforts. Yet internal disturbances, latent heat variations, and ...
Hosted on MSN

Machine Learning Can Predict Intradialytic Hypotension During Hemodialysis

WEDNESDAY, Nov. 6, 2024 (HealthDay News) -- Clinical data and machine learning can help to predict intradialytic hypotension (IDH) for patients undergoing hemodialysis, according to a study published ...
Scientific Research Publishing

An Optimized Port Operation Efficiency Prediction Model Based on ESN and LSTM ()

With the in-depth digital transformation of the global shipping industry, the accurate prediction of smart port operation efficiency has become a key factor in enhancing the competitiveness of ...
IEEE

Multi-channel multi-step spectrum prediction using transformer and stacked Bi-LSTM

Abstract: Spectrum prediction is considered as a key technology to assist spectrum decision. Despite the great efforts that have been put on the construction of spectrum prediction, achieving accurate ...
C&EN

Fault Diagnosis of the Dynamic Chemical Process Based on the Optimized CNN-LSTM Network

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Deep learning provides new ideas for chemical process fault diagnosis, reducing ...
Scientific Research Publishing

Logistics Demand Forecast of Fresh Food E-Commerce Based on Bi-LSTM Model ()

Fresh products have the characteristics of perishable, small batch and high frequency. Therefore, for fresh food e-commerce enterprises, market demand forecasting is particularly important. This paper ...
Frontiers

An Improved Deep Learning Model: S-TextBLCNN for Traditional Chinese Medicine Formula Classification

Purpose: This study proposes an S-TextBLCNN model for the efficacy of traditional Chinese medicine (TCM) formula classification. This model uses deep learning to analyze the relationship between herb ...