Gene expression profiling by microarray technology has been successfully applied to classification and diagnostic prediction of cancers. Various machine learning and data mining methods are currently used for classifying gene expression data. However, these methods have not been developed to address the specific requirements of gene microarray analysis. First, microarray data is characterized b...

In this study, a model for estimating the NFs thermal conductivity by using a GMDH-PNN has been investigated. NFs thermal conductivity was modeled as a function of the nanoparticle size, temperature, nanoparticle volume fraction and the thermal conductivity of the base fluid and nanoparticles. For this purpose, the developed network contains 8 layers with 2 inputs in each layer and also tra...

Through this paper, some performance increasing methods for probabilistic neural network (PNN) are presented. These methods are tested with the glass benchmark database which has an irregular class distribution. Selection of a good training dataset is one of the most important issue. Therefore, a new data selection procedure was proposed. A data replication method is applied to the rare events ...

In most application of the data classifications, the data sets contain both continuous and categorical variables. In other word, multivariate data sets containing mixtures of continuous and categorical variables arise frequently in practice. This paper presents a novel Probability Neural Network (PNN) which can classify the data for both continuous and categorical input data types. The case wit...

A series of organonickel(II) complexes incorporating an amido phosphine ligand tethered with an amino pendant have been prepared and characterized. Deprotonation of N-(dimethylaminoethyl)-2-diphenylphosphinoaniline (H[PNN]) with one equivalent of n-BuLi in ethereal or hydrocarbon solutions at -35 °C generates cleanly dimeric {Li[PNN]}(2) as yellow crystals. The reaction of NiCl(2)(DME) with {Li...

The storage capacity of the Hopfield model is about 15% of the network size. It can be increased significantly in the Potts-glass model of the associative memory only. In this model neurons can be in more than two different states. We show that even greater storage capacity can be achieved in the parametrical neural network (PNN) that is based on the parametrical four-wave mixing process that i...

A text-independent Probabilistic Neural Network (PNN)-based speaker verification system, referred to as WCL-1, is presented. A modular structure, with a distinct PNN for each enrolled speaker, is employed. A gender-dependent universal background model is created to represent the world of possible impostor speakers. Beside portrayal of the WCL-1 system, a comprehensive description of the results...

En Haïti, les parcs nationaux ont été créés pour préserver rares massifs forestiers qui sont constamment menacés par l'agriculture et l'élevage. Toutefois, des études scientifiques sur la dynamique paysagère écosystèmes d’Haïti reçu peu d’attention. Cette étude a objectif de cartographier quantifier perte couverture forestière dans naturels Forêt Pins (PNN-FP2), La-visite (PNN-LV) Macaya (PNN-M...

This paper develops a novel approach to incorporate the contributions of both quantitative validation metrics and qualitative subject matter expert (SME) evaluation criteria in model validation assessment. The relationship between validation metrics (input) and SME scores (output) is formulated as a classification problem, and a probabilistic neural network (PNN) is constructed to execute this ...

PURPOSE The specialized corneal epithelium requires differentiated properties, specific for its role at the anterior surface of the eye. Thus, tight maintenance of the differentiated qualities of the corneal epithelial is essential. Pinin (PNN) is an exon junction component (EJC) that has dramatic implications for corneal epithelial cell differentiation and may act as a stabilizer of the cornea...