Devdiscourse

From disease detection to biomass forecasting: AI improves aquaculture risk strategy

Read more about From disease detection to biomass forecasting: AI improves aquaculture risk strategy on Devdiscourse ...
techwyse.com

Social Media Algorithms 2026 — Threads, Facebook, X, TikTok and Instagram Algorithm Updates

If it feels like social platforms suddenly “get” you more than they used to, you’re not imagining it! In 2026, feeds aren’t only reacting to what you click anymore. They’re predicting what you ...
Scientific Research Publishing

Han, M., Soradi-Zeid, S., Anwlnkom, T. and Yang, Y. (2024) Firefly Algorithm-Based LSTM Model for Guzheng Tunes Switching with Big Data Analysis. Heliyon, 10, e32092.

ABSTRACT: Treatment response prediction remains one of the most pressing challenges in precision psychiatry, where patient heterogeneity and complex biomarker interactions limit the reliability of ...
IEEE

AdaBoost-LSTM: A Hybrid Ensemble Framework for Sequential Credit Card Fraud Detection

Abstract: Credit card fraud detection is a critical task in financial systems, requiring effective algorithms to accurately classify transactions as fraudulent or non-fraudulent. This paper proposes a ...
Frontiers

Life prediction of NC machine tools based on DT technology and LSTM technology

In order to solve the problems of physical model simplification error, insufficient fusion of multi-source monitoring data, and low accuracy of life prediction in traditional CNC machine tool life ...
C&EN

Research on Remaining Useful Life Prediction of PEMWE Stack Based on the LSTM-iTransformer Model

In the context of global energy shortages, traditional energy sources face issues of limited reserves and high prices. As a result, the importance of energy storage technology is increasingly ...
GitHub

Time Series Analysis with LSTM, ARIMA, Prophet, and Anomaly Detection

├── src/ # Source code modules │ ├── lstm_model.py # LSTM implementation with PyTorch │ ├── forecasting_models.py # ARIMA, Prophet, and statistical models │ ├── anomaly_detection.py # Anomaly ...
Scientific Research Publishing

Daungklang, P. and Sathidbhattarasombad, C. (2022) An Experimental Comparison of SES, DES, TES, ARIMA, and LSTM Algorithms for Short Time Series Prediction. Journal of Science ...

ABSTRACT: Forecasting fuel prices is a critical endeavor in energy economics, with significant implications for policy formulation, market regulation, and consumer decision-making. This study ...
ahajournals.org

Using Machine Learning to Risk Stratify Emergency Department Patients With Chest Pain but No Acute Myocardial Infarction: A Multicenter Retrospective Analysis

This study aimed to develop a machine learning‐based model to predict the risk of major adverse cardiac events (MACE) in patients presenting to the emergency department (ED) with chest pain, for whom ...
devdiscourse

Hybrid AI models enhance accuracy and sustainability of solar power forecasting

Researchers have developed a hybrid AI model that significantly improves the accuracy and environmental sustainability of solar power forecasting. The study advances practical tools to support the ...