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11 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.
Hyperparameter Optimization of Bayesian Neural Network Using ...
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14 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 ...
8 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 , ...
18 hours ago · We propose a new yield forecasting algorithm based on Functional Principal Component Analysis (FPCA). •. No seasonal, monthly or any other arbitrary ...
20 hours ago · conducted a comprehensive review of the renewable energy and load forecasting literature using deep learning models and state-of-the-art techniques at ...
6 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 ...
23 hours ago · Literature Review:The literature surrounding the integration of machine learning (ML) technologies into renewable energy processes spans a diverse array of ...
9 hours ago · Introduction. The travel industry is increasingly interested in understanding how customers select among different flight itineraries to travel between a pair ...
29 minutes ago · Detecting cracks in building structures is an essential practice that ensures safety, promotes longevity, and maintains the economic value of the built ...
2 hours ago · The primary objective of this study is to introduce a framework based on ML algorithms to accurately predict cooling loads in buildings. The Decision Tree model ...