Neural Networks in Railways..!!

Neural Networks find extensive applications in areas where traditional computers don’t fare too well. For the longest time possible, the word “intelligence” was just associated with the human brain. Scientists found a way of training computers by following the methodology our brain uses. Thus came Artificial Intelligence, which can essentially be defined as intelligence originating from machines.

To put it even more simply, Machine Learning is simply providing machines with the ability to think, learn and adapt. The applications of Neural Networks across various domains from Social Media and Online Shopping, to Personal Finance, and finally, to the smart assistant on your phone has caused a great impact.

Neural networks are a series of algorithms that mimic the operations of a human brain to recognize relationships between vast amounts of data. They are used in a variety of applications in financial services, from forecasting and marketing research to fraud detection and risk assessment.

In the past 10 years, the best-performing artificial-intelligence systems — such as the speech recognizers on smartphones or Google’s latest automatic translator — have resulted from a technique called “deep learning.”

Deep learning is in fact a new name for an approach to artificial intelligence called neural networks, which have been going in and out of fashion for more than 70 years.

Applications of Neural Network

1) Speech Recognition

2) Character Recognition

3) Signature Verification Application

4)Human Face Recognition and many more..

One of the great Use-case of Neural Network is in Railway Management..!!

Let’s have a look how Railways are using Neural Networks..!!

For decades, the Indian Railways has been a significant and sole way for commutation in the country. Being the third-largest railway network in the world by size, it accommodates and offers its services to people from all walks of life.

Traditionally, the data was being collected manually, and given how large the system is, there were bound to be a few lapses. Indian Railways was looking for a solution that could improve their services offered to the customers and their experience while commuting. So to Solve this Artificial Intelligence is used which uses Neural network which comes under umbrealla of AI.

1) Neural Networks in evaluation of railway track quality condition

Due to the significant costs and time consumed for track visual inspections, most railway industries rely only on geometry data obtained from automated inspections for the assessments of railway track quality conditions. This is the main limitation of the current practices, which may lead to inappropriate determinations of maintenance and repair schedules.

The aim is to provide the possibility of having a rational understanding of the structural defects of track (the causes of track irregularities) without conducting visual inspections. Neural network technique is implemented for this purpose. A vast amount of field data obtained from comprehensive visual and automated inspections of different railways are utilized to develop the neural network models. The results obtained in this research reveals that the neural network technique has a very good capability in establishing correlations between track geometrical defects and track structural problems. The application of the developed models in a number of railway tracks indicates that the proposed methodology is an Effective approach in the prediction of track structural defects.

2) Railway passenger train delay prediction via neural network model

One of the great challenges of using neural network is how to design a superior network for a specific task. To find an appropriate architecture, three different strategies called quick method, dynamic method, and multiple method are investigated. This system uses Neural Network for doing prediction of delay of Railway Passenger Train. By using various NN Algorithms

3) Time-delay neural networks in damage detection of railway bridges

The recent developments in multilayer perceptron using the backpropagation algorithm, has opened up new possibilities in structural identification. Limitation of traditional neural networks (TNN) in dealing with patterns that may vary in time domain has given birth to time-delay neural networks (TDNN). The TNN and the TDNN of Neural Network have been implemented in detecting the damage in bridge structure using vibration signature analysis. A comparative study has been carried out for the various cases of complete as well as incomplete measurement data. It has been observed that TDNNs have performed better than TNNs in this application.

CONCLUSION

There are a lot of Organizations and Government which are improving the Railway management system for providing more benefits to the citizens So By using Such Technologies like Neural Networks, AI. These real world use cases can be solved..!! And in the Future there will be great Railway Management System.

So Through this Small Blog I hope you get some points that how Neural Network is working to solve such demanding challenges of Our Society..!!