In this paper, we propose the design procedure of advanced Polynomial Neural Networks(PNN) architecture fo r optimal model identification of complex and nonlinear system. The proposed PNN architecture is presented as the generic and advanced type. The essence of the design procedure dwells on the Group Method of Data Handling (GMDH). PNN is a flexible neural architecture whose structure is deve...

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 trainin...

During postnatal development, closure of critical periods coincides with the appearance of extracellular matrix structures, called perineuronal nets (PNN), around various neuronal populations throughout the brain. The absence or presence of PNN strongly correlates with neuronal plasticity. It is not clear how PNN regulate plasticity. The repulsive axon guidance proteins Semaphorin (Sema) 3A and...

In Australia, when stormwater systems were first introduced over 100 years ago, they were constructed independently of the sewer systems, and they are normally the responsibility of the third level of government, i.e., local government or city councils. Because of the increasing age of these stormwater systems and their worsening performance, there are serious concerns in a significant number o...

A Probabilistic Neural Network (PNN) is defined as an implementation of statistical algorithm called Kernel discriminate analysis in which the operations are organized into multilayered feed forward network with four layers: input layer, pattern layer, summation layer and output layer. A PNN is predominantly a classifier since it can map any input pattern to a number of classifications. Among t...

In this paper, we introduce the architecture of Genetic Algorithm (GA) based Feed-forward Polynomial Neural Networks (PNNs) and discuss a comprehensive design methodology. A conventional PNN consists of Polynomial Neurons, or nodes, located in several layers through a network growth process. In order to generate structurally optimized PNNs, a GA-based design procedure for each layer of the PNN ...

PURPOSE Pinin (Pnn/DRS/memA) plays an important role in regulating cell-cell adhesion of corneal epithelial cells. In the nucleus, Pnn interacts with both transcriptional repressor and pre-mRNA processing machinery. Here we investigated the consequences of "knocking down" Pnn expression with short hairpin RNAi (shRNAi) on the corneal epithelial cell phenotype. METHODS Cultured human corneal e...

Development of intelligent systems for classifying marine vessels based on their acoustic radiated noise is of major importance in the sonar systems. This paper focuses on three topics. The first topic is applying some modifications to the conventional Probabilistic Neural Network (PNN), as a common classifier in supervised pattern recognition, and suggesting a new configuration of PNN which we...

Predicting the occurrence of disease outbreaks in aquacultural farms can be of considerable value to the long-term sustainable development of the industry. Prior research on disease prediction has essentially depended upon traditional statistical models with varying degrees of prediction accuracy. Furthermore, the application of these models in sustainable aquaculture development and in control...