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Advances in Civil Engineering, 2022 Wind flow on a bluff body is a complex and nonlinear phenomenon that has been mainly studied experimentally or analytically. Several mathematical methods have been developed to predict the wind-induced pressure distribution on bluff bodies; however, most
Josué U. Rodríguez-Alcántara +2 more
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Advances in forecasting with artificial neural networks [PDF]
, 2010 There is decades long research interest in artificial neural networks (ANNs) that has led to several successful applications. In forecasting, both in theoretical and empirical works, ANNs have shown evidence of good performance, in many cases ...
Crone, S, Kourentzes, N
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Study on factor-state artificial neural network model for water quality prediction
浙江大学学报. 农业与生命科学版, 2000 Research on factor neural network theory led to factor-state BP artificial neural network. Combination of informative diffusion with falling shadow technique forms information diffusion falling shadow technique together with factor BP artificial neural ...
GUO Zong-lou, SHEN Wei
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PLoS ONE, 2020 Artificial neural networks are the main tools for data mining and were inspired by the human brain and nervous system. Studies have demonstrated their usefulness in medicine.
Shungo Imai +6 more
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Prediction of Ultimate Bearing Capacity of Skirted Footing Resting on Sand Using Artificial Neural Networks [PDF]
Journal of Soft Computing in Civil Engineering, 2018 The paper presents the prediction of ultimate bearing capacity of different regular shaped skirted footing resting on sand using artificial neural network.
Rakesh Dutta +2 more
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Pricing American Put Option using RBF-NN: New Simulation of Black-Scholes
Moroccan Journal of Pure and Applied Analysis, 2022 The present work proposes an Artificial Neural Network framework for calculating the price and delta hedging of American put option. We consider a sequence of Radial Basis function Neural Network, where each network learns the difference of the price ...
Zaineb El Kharrazi +2 more
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Prediction of Free Swell Index for the Expansive Soil Using Artificial Neural Networks [PDF]
Journal of Soft Computing in Civil Engineering, 2019 Prediction of the free swell index of the expansive soil using artificial neural network has been presented in this paper. Input parameters for the artificial neural network model were plasticity index and shrinkage index, while the output was the free ...
Rakesh Dutta +2 more
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Classification of asteroid families with artificial neural networks [PDF]
Serbian Astronomical Journal, 2020 This paper describes an artificial neural network for classification of asteroids into families. The data used for artificial neural network training and testing were obtained by the Hierarchical Clustering Method (HCM).
Vujičić D. +5 more
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Software Toolkit For Designing An Artificial Neural Network. [PDF]
, 2004 Basically, there are two kinds of artificial neural network (ANN), which can be classified into supervised and unsupervised. Commonly, supervised neural networks are trained or weights adjusted, so that a particular input leads to a specific target ...
Ahmad, M. A., Saleh, J Mohamad
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Research Progress of Oilfield Development Index Prediction Based on Artificial Neural Networks
Energies, 2021 Accurately predicting oilfield development indicators (such as oil production, liquid production, current formation pressure, water cut, oil production rate, recovery rate, cost, profit, etc.) is to realize the rational and scientific development of ...
Chenglong Chen +10 more
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