Implementation of a Neural Network Using Simulator and Petri Nets*

Abstract

This paper describes construction of multilayer perceptron by open source neural networks simulator - Neuroph and Petri net. The described multilayer perceptron solves logical function "xor "- exclusive or. The aim is to explore the possibilities of description of the neural networks by Petri Nets. The selected neural network (multilayer perceptron) allows to be seen clearly the advantages and disadvantages of the realizing through simulator. The selected logical function does not have a linear separability. After consumption of a neural network on a simulator was investigated implementation by Petri Nets. The results are used to determine and to consider opportunities for different discrete representations of the same model and the same subject area.

Authors and Affiliations

Nayden Nenkov, Elitsa Spasova

Keywords

Related Articles

A Multiclass Deep Convolutional Neural Network Classifier for Detection of Common Rice Plant Anomalies

This study examines the use of deep convolutional neural network in the classification of rice plants according to health status based on images of its leaves. A three-class classifier was implemented representing normal...

Requirements Prioritization and using Iteration Model for Successful Implementation of Requirements

Requirements prioritization is ranking of software requirements in particular order. Prioritize requirements are easy to manage and implement while un-prioritized requirements are costly and consume much time as total es...

3D Mapping based-on Integration of UAV Platform and Ground Surveying

Development in aerial photogrammetry technology has contributed a notable impact to the area of large-scale mapping. Nowadays, unmanned aerial vehicle (UAV) platform has become a significant tool in aerial mapping. Gener...

A Bayesian Approach to Predicting Water Supply and Rehabilitation of Water Distribution Networks

Water distribution network (WDN) consists of several elements the main ones: pipes and valves. The work developed in this article focuses on a water supply prediction in the short and long term. To this end, reliability...

An Investigation into the Suitability of k-Nearest Neighbour (k-NN) for Software Effort Estimation

Software effort estimation is an increasingly significant field, due to the overwhelming role of software in today’s global market. Effort estimation involves forecasting the effort in person-months or hours required for...

Download PDF file
  • EP ID EP128119
  • DOI 10.14569/IJACSA.2016.070155
  • Views 99
  • Downloads 0

How To Cite

Nayden Nenkov, Elitsa Spasova (2016). Implementation of a Neural Network Using Simulator and Petri Nets*. International Journal of Advanced Computer Science & Applications, 7(1), 412-417. https://europub.co.uk/articles/-A-128119