Two different artificial neural networks (NN) are used for estimating a time dependent boundary condition (x = 0) in a slab: multilayer perceptron (MP) and radial base function (RBF). The input for the NN is the temperature time-series obtained from a probe next to boundary of interest. Our numerical experiments follow the work of Krejsa et al. [4]. The NNs were trainned considering 5 per cent ...

An involution is a permutation that is its own inverse. Given a permutation σ of [n], let Nn(σ) denote the number of ways to write σ as a product of two involutions of [n]. If we endow the symmetric groups Sn with uniform probability measures, then the random variables Nn are asymptotically lognormal. The proof is based upon the observation that, for most permutations σ, Nn(σ) can be well appro...

A multilayer perceptron (MLP) artificial neural network (NN) was trained with Monte Carlo data to detect b-jets. A variety of NNs were tested to maximize performance. The best NN was run on data with different reconstruction options. It was found that a simple MLP NN with 6 variables and 6 hidden neurons performed better than using only a decay length significance cut for detecting b-jets. The ...

Recently developed chiral nucleon-nucleon (NN) forces at next-to-leading order (NLO), that describe NN phase shifts up to about 100 MeV fairly well, have been applied to 3N and 4N systems. Faddeev-Yakubovsky equations have been solved rigorously. The resulting 3N and 4N binding energies are in the same range as found using standard NN potentials. In addition, low-energy 3N scattering observable...

This paper proposes a new method for the extraction of knowledge from a trained type feed-forward neural network. The new knowledge extracted is expressed by fuzzy rules directly from a sensibility analysis between the inputs and outputs of the relationship that model the neural network. This easy method of extraction is based on the similarity of a fuzzy set with the derivative of the tangent ...

In rats and mice, 1-nitronaphthalene (1-NN) produces both lung and liver toxicity. Even though these toxicities have been reported, the metabolism and disposition of 1-NN have not been elucidated. Therefore, studies were performed to characterize its fate after i.p. and i.v. administration to male Sprague-Dawley rats. After i.p. administration of [C]1-NN (100 mg/kg; 60 mCi/kg), 84% of the dose ...

In Neural Networks (NN), Adaptive Activation Functions (AAF) have parameters that control the shapes of activation functions. These parameters are trained along with other parameters in the NN. AAFs have improved performance of Neural Networks (NN) in multiple classification tasks. In this paper, we propose and apply AAFs on feedforward NNs for regression tasks. We argue that applying AAFs in t...

This paper presents an iterative learning controller using neural network (NN) for the robot trajectory tracking control. Basic control configuration is briefly presented and a new weight-tuning algorithm of NN is proposed with a dead-zone technique. Theoretical proof is given which shows that our modified algorithm guarantees the convergence of NN estimation error in the presence of disturbanc...