AZoBuild on MSN

AI Model Restores Lost Bridge Data to Improve Structural Safety

BiGRU, a deep learning model that enhances data recovery in structural health monitoring, ensuring the reliability of bridge ...

Which Machine Learning Models Are Most Used In Crypto Signal Generation?

Machine learning is transforming how crypto traders create and understand signals. From supervised models such as Random Forests and Gradient Boosting Machines to sophisticated deep learning hybrids ...
Frontiers

Brain-Inspired and neurally grounded algorithms in learning and control of advanced robots

In recent years, the field of robotics has undergone significant transformation, driven increasingly by advances in brain-inspired and neurally grounded ...
Frontiers

Advancing Computational Material Science and Mechanics through Integrated Deep Learning Models

The field of computational materials science has been profoundly transformed by integrating deep learning and other machine learning methodologies. These sophisticated data-driven approaches have ...
The Malaysian Reserve

Cognizant’s AI Lab Announces Breakthrough Research for Fine-Tuning LLMs and Records its 61st U.S. Patent Issuance

Cognizant (Nasdaq: CTSH) today announced a breakthrough from its AI Lab that introduces a novel, efficiency-focused method ...
Scientific Research Publishing

Research on Prediction of Air Quality CO Concentration Based on Python Machine Learning ()

Wang, Z. (2025) Research on Prediction of Air Quality CO Concentration Based on Python Machine Learning. Advances in Internet ...

Indian Forex Market Sees 70% Jump in AI Trading Success

AI has transformed the forex market by reshaping trading strategies and outcomes. Traders now approach currency markets differently, and AI tools help create better trading platforms. Algorithmic ...
Devdiscourse

How AI transforms solar energy management and storage

According to the analysis, deep learning architectures such as Long Short-Term Memory (LSTM) networks and hybrid CNN-LSTM ...
Devdiscourse

AI-powered forecasting boosts retail efficiency: LSTM outshines traditional models

Demand forecasting remains one of the most complex challenges in retail management. As consumer behavior evolves rapidly, ...
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What Is MaxOut in Deep Learning – Intuition and Explanation

Discover what MaxOut is and why it matters in deep learning. Understand the intuition, math, and use cases behind this activation function. #MaxOut #DeepLearning #NeuralNetworks Trump wants to ‘end’ ...
IEEE

Physics-Enhanced Transfer Learning for the State-of-Charge Estimation of Spacecraft Li-Ion Batteries Using Bi-LSTM Networks

Abstract: In this work, the problem of state-of-charge (SOC) estimation for batteries with different chemical properties and different operating conditions is investigated based on a physics-enhanced ...
IEEE

Towards Generalizable Meta-Deep Reinforcement Learning Algorithm for Multi-Objective Traveling Salesman Problems

Abstract: The multi-objective traveling salesman problem (MOTSP) is a representative class of multi-objective combinatorial optimization problems, with significant implications for both theoretical ...