Journal ArticleDOI
Modeling of solar energy systems using artificial neural network: A comprehensive review
Ammar H. Elsheikh,Ammar H. Elsheikh,Swellam W. Sharshir,Mohamed Abd Elaziz,Mohamed Abd Elaziz,Abd Elnaby Kabeel,Wang Guilan,Zhang Haiou +7 more
TLDR
An attempt has been made to scrutinize the applications of artificial neural network (ANN) as an intelligent system-based method for optimizing and the prediction of different solar energy devices’ performance.About:
This article is published in Solar Energy.The article was published on 2019-03-01. It has received 389 citations till now. The article focuses on the topics: Photovoltaic system & Solar energy.read more
Citations
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Journal ArticleDOI
Deep solar radiation forecasting with convolutional neural network and long short-term memory network algorithms
TL;DR: It is ascertained that a proposed hybrid model based on a convolution network framework can accurately predict GSR and enable energy availability to be regularly monitored over multi-step horizons when coupled with a low latency Long Short-Term Memory network.
Journal ArticleDOI
A review of melting and freezing processes of PCM/nano-PCM and their application in energy storage
Sara Rostami,Masoud Afrand,Amin Shahsavar,Mohsen Sheikholeslami,Rasool Kalbasi,Saeed Aghakhani,Mostafa Safdari Shadloo,Hakan F. Oztop +7 more
TL;DR: In this article, a detailed illustration of phase change materials and their working principle, different types, and properties are provided, and a characteristic example of PCM in solar energy storage and the design of PCMs are reviewed and analyzed.
Journal ArticleDOI
Machine learning technology in biodiesel research: A review
Mortaza Aghbashlo,Mortaza Aghbashlo,Wanxi Peng,Meisam Tabatabaei,Soteris A. Kalogirou,Salman Soltanian,Homa Hosseinzadeh-Bandbafha,Omid Mahian,Omid Mahian,Su Shiung Lam,Su Shiung Lam +10 more
TL;DR: This paper is devoted to thoroughly reviewing and critically discussing various ML technology applications, with a particular focus on ANN, to solve function approximation, optimization, monitoring, and control problems in biodiesel research.
Journal ArticleDOI
Review on sun tracking technology in solar PV system
Anshul Awasthi,Akash Kumar Shukla,S R Murali Manohar,Chandrakant Dondariya,Komal Shukla,Deepak Porwal,Geetam Richhariya +6 more
TL;DR: This paper mainly focuses on the design and performance analysis of the various dual-axis tracking solar systems proposed in recent years and has proved to be more efficient and advantageous than its single-axis and fixed counterparts.
Journal ArticleDOI
An enhanced productivity prediction model of active solar still using artificial neural network and Harris Hawks optimizer
TL;DR: A new productivity prediction model of active solar still was developed depending on improving the performance of the traditional artificial neural networks using Harris Hawks Optimizer, which had the best accuracy in predicting the solar still yield compared with the real experimental results.
References
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Finding Structure in Time
TL;DR: A proposal along these lines first described by Jordan (1986) which involves the use of recurrent links in order to provide networks with a dynamic memory and suggests a method for representing lexical categories and the type/token distinction is developed.
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Neural Networks And Learning Machines
TL;DR: Refocused, revised and renamed to reflect the duality of neural networks and learning machines, this edition recognizes that the subject matter is richer when these topics are studied together.
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Radial Basis Functions, Multi-Variable Functional Interpolation and Adaptive Networks
David S. Broomhead,David Lowe +1 more
TL;DR: The relationship between 'learning' in adaptive layered networks and the fitting of data with high dimensional surfaces is discussed, leading naturally to a picture of 'generalization in terms of interpolation between known data points and suggests a rational approach to the theory of such networks.
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Wavelet networks
Qinghua Zhang,Albert Benveniste +1 more
TL;DR: A wavelet network concept, which is based on wavelet transform theory, is proposed as an alternative to feedforward neural networks for approximating arbitrary nonlinear functions.
Journal ArticleDOI
Artificial neural networks in renewable energy systems applications: a review
TL;DR: In this article, the authors present various applications of neural networks mainly in renewable energy problems in a thematic rather than a chronological or any other order, which clearly suggest that artificial neural networks can be used for modelling in other fields of renewable energy production and use.