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Forecasting gold price changes: Rolling and recursive neural network models
(2008)
This paper analyzes recursive and rolling neural network models to forecast one-step-ahead sign variations in gold price. Different combinations of techniques and sample sizes are studied for feed forward and ward neural ...
Interplay between Notch signaling and the homeoprotein Xiro1 is required for neural crest induction in Xenopus embryos
(2004)
The neural crest is a population of cells that originates at
the interface between the neural plate and non-neural
ectoderm. Here, we have analyzed the role that Notch and
the homeoprotein Xiro1 play in the specification ...
Neural Network Prediction Interval Based on Joint Supervision
(Institute of Electrical and Electronics Engineers Inc., 2018)
In this paper, a new prediction interval model based on a joint supervision loss function for capturing the uncertainties associated with the modeled phenomenon is described. This model provides the upper and lower bounds ...
Failure mode detection of reinforced concrete shear walls using ensemble deep neural networks
(Springer, 2022)
Reinforced concrete structural walls (RCSWs) are one of the most efficient lateral force-resisting systems used in buildings, providing sufficient strength, stiffness, and deformation capacities to withstand the forces ...
Multivariable predictive control of a pressurized tank using neural networks
(SPRINGER, 2006-03)
The behavior of a multivariable predictive control scheme based on neural networks applied to a model of a nonlinear multivariable real process, consisting of a pressurized tank is investigated in this paper. The neural ...
Logistic regression and neural network classification of seismic records
(Elsevier, 2013)
The identification of seismic records in seismically active mines is examined by considering logistic regression and neural network classification techniques. An efficient methodology is presented for applying these ...
Asymmetry in neural fields: a spatiotemporal encoding mechanism
(Springer-Verlag, 2013-01-08)
Neural field models have been successfully
applied to model diverse brain mechanisms like visual attention,
motor control, and memory. Most theoretical and modelingworks
have focused on the study of the dynamics of ...
Neural and statistical predictors for time to readmission in emergency departments: A case study
(Elsevier B.V., 2019)
© 2019 The prediction of readmissions in the healthcare system, i.e. patients that are discharged and come back in a short interval of time, has taken great importance as readmissions have been taken as a measure of the ...
Computational modelling of the effects of aging on syntactic processing in Spanish: A study using neural networks Modelamiento computacional de los efectos del envejecimiento sobre el procesamiento sintáctico en español: Un estudio mediante redes neuronal
(2011)
The focus of this article is the application of artificial neural networks to the quantification of the effects of aging on syntactic processing of complex sentences in Spanish. The network models studied were able to ...
Existence and global convergence of periodic solutions in recurrent neural network models with a general piecewise alternately advanced and retarded argument
(Kluwer Academic Publishers, 2014)
This paper is concerned with existence, uniqueness and global exponential stability of a periodic solution for recurrent neural network described by a system of differential equations with piecewise constant argument of ...