Using machine learning and math, a BYU student improved a key tool firefighters rely on during wildfire season ...

In today’s increasingly digital economy, utility providers — whether delivering electricity, gas, water, or broadband — ...

All 243 Jupyter Notebook 190 Python 39 HTML 5 R 2 C++ 1 Go 1 TypeScript 1. ... Predicting abalone age (ring count) using a Random Forest Regressor. The model is deployed via a FastAPI backend for ...

Prediction of meteorological phenomena using conventional techniques is always a challenge for meteorologists. We developed a novel method for predicting meteorological phenomena by using the Random ...

We trained Random Forest classifier to predict “mortality” for patients hospitalized with COVID-19. Results: Based on the interpretability of the model, age emerged as the primary predictor of ...

Predicting Atmospheric Particle Phase State Using an Explainable Machine Learning Approach Based on Particle Rebound Measurements. ... Mapping the personal PM2.5 exposure of China's population using ...

Downscaling GRACE total water storage data using random forest: ... The contribution of remote sensing and input feature selection for groundwater level prediction using LSTM neural networks in the ...

Abstract. Objective: This study aimed to develop a predictive model using a random forest algorithm to determine the likelihood of postoperative adhesive small bowel obstruction (ASBO) in infants ...