17 hours ago · Hence, this paper provides a state-of-the-art review of the five most popular and advanced ANN models for PV power forecasting.

20 hours ago · Abstract. This paper proposes a new hybrid framework for short-term load forecasting (STLF) by combining the Feature Engineering (FE) and Bayesian Optimization ...

13 hours ago · In this paper, a new artificial neural network (ANN) model is developed to accurately predict Vs as a function of porosity ( ), gamma-ray (GR), bulk density , ...

5 hours ago · ing Fuzzy Neural Network Models​​ This chapter focuses on the design and implementation of a fuzzy-neuro based weather forecasting agent, iJADE WeatherMan, which ...

23 hours ago · We propose a new yield forecasting algorithm based on Functional Principal Component Analysis (FPCA). •. No seasonal, monthly or any other arbitrary ...

3 hours ago · Graph neural networks (GNNs) play a crucial role in fusing multiple types of sensor data for machinery fault diagnosis by capturing complex relationships ...

14 hours ago · Introduction. The travel industry is increasingly interested in understanding how customers select among different flight itineraries to travel between a pair ...

4 hours ago · In this research endeavor, we employed a diverse set of five machine learning methodologies, specifically, decision trees, random forests, logistic regression, ...

24 hours ago · ... introduction” focuses on lecture specifics like syllabus, overview, and prerequisites. “Instructor” evaluates qualities like expertise and teaching style ...

5 hours ago · The tutorial will aim to provide a comprehensive guide on Neural Architecture Search a category of methods designed to adapt the structures of the network ...