Grasshopper-inspired AI boosts emergency resource prediction

A hybrid artificial intelligence (AI) system modeled on grasshopper behavior could help allocate medical resources, transport and power during an urban emergency, according to research in the ...

Xiangtian Hui Examines Machine Learning and Data Engineering Methods for Healthcare Data Systems and Cancer Informatics

A body of healthcare AI research connects data infrastructure, machine learning, and natural language processing across ...
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 ...
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

The monitoring condition of the cable laying conveyor, such as rotational speed, driving current, and side pressure, reflects the real-time operation status of the cable laying process. Accurate ...
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 ...
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 ...
Scientific Research Publishing

Michańków, P., Oleksy, P., & Stankiewicz, M. (2022). Application of LSTM Networks in Forecasting the Value of BTC and the S&P500 Index. Journal of Financial Algorithms and ...

ABSTRACT: This paper presents a comprehensive approach to developing effective trading strategies for Exchange-Traded Funds (ETFs) by leveraging Long Short-Term Memory (LSTM) networks and sentiment ...