in this paper, we introduce a takagi-sugeno (ts) fuzzy model which is derived from a typical multi-layer perceptron neural network (mlp nn). at first, it is shown that the considered mlp nn can be interpreted as a variety of ts fuzzy model. it is discussed that the utilized membership function (mf) in such ts fuzzy model, despite its flexible structure, has some major restrictions. after modify...

CONTEXT Ghrelin is a peptide with multiple functions that circulates in acylated (AG) and unacylated (UAG) forms. However, the role of ghrelin in neonates (NN) remains to be clarified. OBJECTIVE The aim of this study was to determine ghrelin concentrations of the two forms in NN to clarify their biological roles. As such, ghrelin levels at birth were compared with those in later life. SETTI...

Host-guest complexes of tris(NN-CH2)-substituted 1,4,7-triazacyclononane and tetrakis(NN-CH2)-substituted 1,4,7,10-tetraazacyclododecane afforded the folded structures of the hosts where the NN radical oxygen atoms were coordinated to the guest metal ion, leading to enhanced antiferromagnetic couplings in the solid state and an ESR line broadening in the solution phase (NN = 4,4,5,5-tetramethyl...

A k nearest neighbor (k-NN) query retrieves k objects in a given objects set which are closest to the query point q. Processing continuous k-nearest neighbor (k-NN) query over moving objects in location-dependent application requires that the frequent location updates of moving objects and intensive continuous k-NN queries must be efficiently processed at the same time. In this paper, we propos...

Euclidean distance -nearest neighbor ( -NN) classifiers are simple nonparametric classification rules. 5 5 Bootstrap methods, widely used for estimating the expected prediction error of classification rules, are motivated by the objective of calculating the ideal bootstrap estimate of expected prediction error. In practice, bootstrap methods use Monte Carlo resampling to estimate the ideal boot...

[1] A group of geophysical applications, which from the mathematical point of view, can be formulated as complex, multidimensional, nonlinear mappings and which in terms of the neural network (NN) technique, utilize a particular type of NN, the multilayer perceptron (MLP), is reviewed in this paper. This type of NN application covers the majority of NN applications developed in geosciences like...

We investigate the influence of morphology and size on the vibrational properties of disordered clusters of colloidal particles with attractive interactions. Spectral features of the vibrational modes are found to depend strongly on the average number of nearest neighbors, NN, but only weakly on the number of particles in each glassy cluster. In particular, the median phonon frequency, ω(med), ...

Neural Networks (NN) hold the potential for improving a variety of tasks in remote sensing and image processing. They represent a different approach to problems, as they do not rely on statistical relationships. Instead, neural networks adaptively estimate continuous functions from data without specifying mathematically how outputs depend on inputs. This paper evaluates the effect of metrics se...