Abstract: In Internet of Things (IoT)-enabled energy systems, accurate wind power forecasting is essential for intelligent scheduling and grid stability. However, meteorological and power time series ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. This study explores the development of two predictive models for the yield sooting ...
ABSTRACT: The glycemic index (GI) is a qualitative indicator of the glycemic response of a carbohydrate food. Its variability is due to the composition of the food, which in turn is related to the ...
Traffic forecasting is crucial for a variety of applications, including route optimization, signal management, and travel time estimation. However, many existing prediction models struggle to ...
The MNIST dataset is a set of 70,000 human-labeled 28 x 28 greyscale images of individual handwritten digits. It is a subset of a larger dataset available from NIST - The National Institute of ...
For predicting relapse in 1,387 patients with early-stage (I-II) NSCLC from the Spanish Lung Cancer Group data (average age 65.7 years, female 24.8%, male 75.2%), we train tabular and graph machine ...
Machine learning (ML) approaches are a collection of algorithms that attempt to extract patterns from data and to associate such patterns with discrete classes of samples in the data—e.g., given a ...
Despite being quite effective in a variety of tasks across industries, deep learning is constantly evolving, proposing new neural network (NN) architectures such as the Spiking Neural Network (SNN).
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