Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
Machine learning based solar photovoltaic power forecasting: A review and comparison
The growing interest in renewable energy and the falling prices of solar panels place solar
electricity in a favourable position for adoption. However, the high-rate adoption of …
electricity in a favourable position for adoption. However, the high-rate adoption of …
A review on global solar radiation prediction with machine learning models in a comprehensive perspective
Global solar radiation information is the basis for many solar energy utilizations as well as
for economic and environmental considerations. However, because solar-radiation …
for economic and environmental considerations. However, because solar-radiation …
Analysis of different combinations of meteorological parameters in predicting the horizontal global solar radiation with ANN approach: A case study
Solar energy is a clean renewable energy source and availability of solar resources at a
particular location depends on the local meteorological parameters. In the present study …
particular location depends on the local meteorological parameters. In the present study …
Performance comparison of two global solar radiation models for spatial interpolation purposes
In this paper, two monthly global solar radiation spatial interpolating models: an Artificial
Neural Network (ANN) and an Inverse Distance Weighting based model (IDW) have been …
Neural Network (ANN) and an Inverse Distance Weighting based model (IDW) have been …
[HTML][HTML] Intelligence techniques in sustainable energy: analysis of a decade of advances
In the last decade, many artificial intelligence (AI) techniques have been used to solve
various problems in sustainable energy (SE). Consequently, an increasing volume of …
various problems in sustainable energy (SE). Consequently, an increasing volume of …
New void fraction equations for two-phase flow in helical heat exchangers using artificial neural networks
In this research, two new empirical equations based on Artificial Neural Network (ANN) were
developed to determine the new void fraction in two-phase flow inside helical vertical coils …
developed to determine the new void fraction in two-phase flow inside helical vertical coils …
[HTML][HTML] AI-Driven precision in solar forecasting: Breakthroughs in machine learning and deep learning
The need for accurate solar energy forecasting is paramount as the global push towards
renewable energy intensifies. We aimed to provide a comprehensive analysis of the latest …
renewable energy intensifies. We aimed to provide a comprehensive analysis of the latest …
[HTML][HTML] Heat transfer coefficients analysis in a helical double-pipe evaporator: Nusselt number correlations through artificial neural networks
In this study, two empirical correlations of the Nusselt number, based on two artificial neural
networks (ANN), were developed to determine the heat transfer coefficients for each section …
networks (ANN), were developed to determine the heat transfer coefficients for each section …
Artificial neural network applied to the renewable energy system performance
Artificial neural networks (ANNs), inspired by human learning, have allowed an optimal
solution to problems in different fields of knowledge. The precise representations of the …
solution to problems in different fields of knowledge. The precise representations of the …
[کتاب][B] Artificial Neural Networks for Renewable Energy Systems and Real-World Applications
AH Elsheikh, M Abd Elaziz - 2022 - books.google.com
Artificial Neural Networks for Renewable Energy Systems and Real-World Applications
presents current trends for the solution of complex engineering problems in the application …
presents current trends for the solution of complex engineering problems in the application …