The study demonstrates machine learning's role in predicting compressive strength of rice husk ash concrete, aiding the shift ...

Dr. James McCaffrey presents a complete end-to-end demonstration of decision tree regression from scratch using the C# language. The goal of decision tree regression is to predict a single numeric ...

In an era where insurance fraud drains billions from the global economy annually, a groundbreaking study by researchers ...

Smart health refers to the integration of cutting-edge technologies into healthcare systems to improve patient care and apply ...

A team of Kenyan researchers has developed an artificial intelligence–based hybrid model capable of predicting food prices with unprecedented accuracy, offering a new data-driven tool to support food ...

This analysis uses Bristol Airbnb listing data to predict rental prices through machine learning techniques. The dataset contains comprehensive information about Airbnb properties including location ...

1 Department of Civil and Environmental Engineering, Hanyang University, Seoul, Republic of Korea 2 Department of Civil and Mineral Engineering, University of Toronto, Toronto, ON, Canada Accurate ...

I have successfully run the deep learning models. However, when I run the Gradient Boosting Regression model, the predictions collapse into a straight flat line. I would like to understand why this ...

Researchers have developed a hybrid machine learning model combining Gradient Boosting Regression Trees with Bayesian Optimization to accurately predict the compressive strength of self-compacting ...

In response to environmental degradation and diminishing fossil fuel reserves, there is an urgent global shift toward sustainable and cleaner energy solutions. Hydrogen has gained importance as an ...

This study explores the potential of nano-graphene particles for the sustainable manufacturing of concrete. The primary goal is to predict the compressive strength of graphene-incorporated concrete by ...