Reliability of Modeling and Optimization for Railway Network Using Three Layers Perceptron Neural Network

Document Type : Original Article

Authors
Fatemeh Hajizadeh 1
Saeed Ghazi maghrebi 2
1 Ph.D., Student, Department of Electrical and Computer Engineering, Yadegar-e-Imam Khomeini (RAH) Shahre Rey Branch, Islamic Azad University, Tehran, Iran.
2 Associate Professor, Department of Electrical and Computer Engineering, Yadegar-e-Imam Khomeini (RAH) Shahre Rey Branch, Islamic Azad University, Tehran, Iran.
10.22034/road.2023.364256.2101
Abstract
Today, a huge amount of data is transmitted around the world through the high capacity of optical telecommunication networks. In railways, optical transmission telecommunication networks play a very important role in the transmission of critical a large amount of rail data. Reliability of telecommunication infrastructure is required to increase productivity, maintain safety and reduce maintenance costs. In this article, the existing reliability level and all relevant parameters (the number of network outages and the time between network failures, MTBF) of the railway optical transmission telecommunication network are obtained through the Reliability block diagram method and simulated through the Monte Carlo method and then optimized. Also, prediction of the network's behavior and obtaining the probability of its failures are done through three-layer perceptron neural networks and the results are presented. The network implemented in this article is the 654 km long optical telecommunication transmission network of the railway region of Azerbaijan.
Keywords
Optical Transmission Telecommunication Network
Reliability
Monte Carlo Simulation
Perceptron Neural Network
RBD Model
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