In the last decade, neural networks have drawn noticeable attention from many computer and operations researchers. While some previous studies have found encouraging results with using this artificial intelligence technique to predict the movements of established financial markets, it is interesting to verify the persistence of this performance in the emerging markets. These rapid growing finan...

En la Amazonía colombiana, constitución de Zonas Reserva Campesina (ZRC) ha sido un proceso históricamente marcado por estigmatización y parsimonia del Estado que además una postura opuesta a compatibilidad presencia humana con conservación los Parques Nacionales Naturales (PNN), también promovido actividades extractivistas en el territorio. A partir caso ZRC Losada Guayabero, contigua (PNN) Ti...

The ability of the environment to shape cortical function is at its highest during critical periods of postnatal development. In the visual cortex, critical period onset is triggered by the maturation of parvalbumin inhibitory interneurons, which gradually become surrounded by a specialized glycosaminoglycan-rich extracellular matrix: the perineuronal nets. Among the identified factors regulati...

Abstract This paper put forward a new interactive design approach for customized garments towards sustainable fashion using machine learning techniques, including radial basis function artificial neural network (RBF ANN), genetic algorithms (GA), probabilistic (PNN), and support vector regression (SVR). First, RBF ANNs were employed to estimate the detailed human body dimensions fulfill consume...

We introduce a concept of self-organizing Hybrid Neurofuzzy Networks (HNFN), a hybrid modeling architecture combining neurofuzzy (NF) and polynomial neural networks(PNN). The development of the Self-organizing HNFN dwells on the technologies of Computational Intelligence (CI), namely fuzzy sets, neural networks, and genetic algorithms. The architecture of the Self-organizing HNFN results from a...

Semi-empirical frameworks are widely used in calculating the bandhead energies of three-quasiparticle (3qp) configurations observed well-deformed odd-A nuclei. In present study, our aim is to improve previous version semi-empirical model [Physical Review C. 1992, 45(6), 3013]. This achieved by incorporating ignored vital contributions owing irrotational motion valance protons/neutrons, diagonal...

Probabilistic Neural Network (PNN) also termed to be a learning machine is preliminarily used with an extension of various image classifications based on Training networks and Testing networks. To efficiently detect Brain Tumor cells, clustering method based on FCM can also be implemented. The Probabilistic Neural Network (PNN) will be employed to classify the various stages of Tumor cut levels...

In this work an active learning PNN was used to recognize instrumental sounds. LPC and MFCC coefficients with different orders were used as features. The best analysis orders were found by using passive PNNs and these sets were used with active learning PNNs. By realizing some experiments, it was shown that the entire performance was improved by using the active learning algorithm.

Handwritten digit recognition can be categorized as a classification problem. Probabilistic Neural Network (PNN) is one of the most effective and useful classifiers, which works based on Bayesian rule. In this paper, in order to recognize Persian (Farsi) handwritten digit recognition, a combination of intelligent clustering method and PNN has been utilized. Hoda database, which includes 80000 P...