IEEE

Deep Learning-Based Control of Active Power Filters Using LSTM and GRU Networks for Harmonic and Frequency Estimation

Abstract: Deep Learning (DL) techniques provide a powerful tool enhancing the learning capabilities of the neural networks (NN), and are increasingly applied in the field of electric power systems. In ...
Scientific Research Publishing

Applying Deep Learning Techniques for Automated Analysis and Interpretation of Financial Statements ()

Multimodal Learning, Deep Learning, Financial Statement Analysis, LSTM, FinBERT, Financial Text Mining, Automated Interpretation, Financial Analytics Share and Cite: Wandwi, G. and Mbekomize, C. (2025 ...

What is the Difference Between Deep Learning and Machine Learning

We have explained the difference between Deep Learning and Machine Learning in simple language with practical use cases.
Beebom

What is Deep Learning in AI? Understanding How AI Really Works

Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter adjustments. It started with the ...
Scientific Research Publishing

Li, W. and Becker, D.M. (2021) Day-Ahead Electricity Price Prediction Applying Hybrid Models of LSTM-Based Deep Learning Methods and Feature Selection Algorithms under ...

ABSTRACT: Accurate forecasting of the system marginal price (SMP) is crucial to improve demand-side management and optimize power generation scheduling. However, predicting the SMP is challenging due ...
Frontiers

A physical state prediction method based on reduce order model and deep learning applied in virtual reality

The application of virtual reality (VR) in industrial training and safety emergency needs to reflect realistic changes in physical object properties. However, existing VR systems still lack fast and ...
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 ...
IEEE

Enhancing Creativity and Validation in Explanatory Deep Learning-Based Symbolic Music Generation: A Hybrid Approach With LSTM and Genetic Algorithms

Abstract: This research proposes an explanatory deep learning-based music generation approach, where the output of a deep learning model is validated through a set of predefined musical rules, with a ...
Wired

Google DeepMind’s AI Agent Dreams Up Algorithms Beyond Human Expertise

A key question in artificial intelligence is how often models go beyond just regurgitating and remixing what they have learned and produce truly novel ideas or insights. A new project from Google ...