AZoRobotics on MSN

AI Tool Uses EEG Signals to Support Early Dementia Diagnosis

University researchers collaborated with institutions across the globe to develop two new AI models for improved dementia detection.
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 ...
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 ...
C&EN

SOH Estimation Based on Multisource Feature Extraction and SSA-LSTM Algorithm

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. In contrast, data-driven methods do not rely on fixed models or ...
Frontiers

Cable laying conveyor state prediction and fault warning based on attention-driven CNN-LSTM algorithm

1 State Grid Wuxi Power Supply Company, Wuxi, China 2 Department of Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China The monitoring condition of the cable laying conveyor, such ...
IEEE

Option-Based Deep Reinforcement Learning for Topology Control of Power Systems

Abstract: In this paper, we propose an option-based deep reinforcement learning (DRL) algorithm called option-critic with long short-term memory (OC-LSTM), which combines the option-critic (OC) ...
IEEE

A Novel Hybrid GCN-LSTM Algorithm for Energy Stock Price Prediction: Leveraging Temporal Dynamics and Inter-Stock Relationships

Abstract: Energy stock price prediction is a pivotal challenge in financial forecasting, characterized by high volatility and complexity influenced by geopolitical factors, regulatory shifts, and ...
GitHub

ISCO Community of Practice

15:45-16:05 Ecuador: Coding Occupations in the Population and Housing Census (Presentation Slides) Diana Méndez and Victor Espinoza, INEC 16:05-16:25 USA: Autocoding in the Occupational Employment and ...
Frontiers

Real-time fault detection for IIoT facilities using GA-Att-LSTM based on edge-cloud collaboration

With the rapid development of Industrial Internet of Things (IIoT) technology, various IIoT devices are generating large amounts of industrial sensor data that are spatiotemporally correlated and ...