Devdiscourse

High-accuracy AI models improve IoT threat detection

The results show that the Decision Tree model emerged as the top-performing algorithm, achieving an accuracy rate of 99.36 percent. Random Forest followed closely with 99.27 percent accuracy, while ...
Frontiers

Computational Frameworks for Decision-Making: From Bayesian Inference to Reinforcement Learning Models

The ability to make adaptive decisions in uncertain environments is a fundamental characteristic of biological intelligence. Historically, computational ...

Machine learning tool pinpoints optimal locations for tree planting, offering a powerful tool for climate mitigation

Afforestation—establishing forests on previously non-forested land, or where forests have not existed for a long time—is one ...
IEEE

A Reinforcement Learning Algorithm for Safety Decision Making in Autonomous Driving Systems with Reward Machine Guidance

Abstract: In the field of autonomous driving, safe and efficient decision-making through deep reinforcement learning remains a significant challenge. Existing methods often struggle to adapt to the ...
IEEE

Tree-Based Machine Learning Algorithms for Alzheimer's Disease Prediction

Abstract: Alzheimer's disease (AD) is the leading cause of dementia among elder people above the age of 65 years. Currently, there is no definitive treatment for AD. Early detection of AD is essential ...
Hosted on MSN

Powerful machine safely handling tall tree removal

A powerful heavy machine is used to safely handle and remove tall trees in a controlled environment. With its extended arm and precision tools, the machine allows operators to manage difficult tasks ...