Neural Network is an information processing paradigm that is inspired by the way biological nervous systems, such as the brain which process information. The main element is the novel structure of the information processing system. It is composed of a large number of highly interconnected processing elements called neurons working in unison to solve specific problems. A neural network contains layers of interconnected nodes. Each node is a perception and is similar to a multiple linear regression. The perceptron feeds the signal produced by a multiple linear regression into an activation function that may be nonlinear. A neural network is configured for a specific application, such as pattern recognition or data classification, through a learning process. Learning in biological systems involves adjustments to the synaptic connections that exist between the neurons.
Application of Neural Networks
The neural network in robotics
The very prominent application for the neural network in robotics is an autonomous vehicle such as an autonomous robot vehicle. Medical robots or ambulance robots that can deliver medical supplies and on-screen instructions. Next could be service robots like a dog robot.
To analyze natural disasters
Artificial neural networks have been used to accelerate reliability analysis of infrastructures subject to natural disasters.
Neural networks are best at identifying patterns or trends in data, they are well suited for prediction or forecasting needs including sales forecasting, industrial process control, customer research, data validation, risk management, target marketing, etc. A neural network evaluates price data and unearths opportunities for making trade decisions based on the data analysis.
Neural networks in medicine
Neural networks in medicine, it will receive an extensive application to biomedical systems in the next few years. The research is mostly on modeling parts of the human body and recognizing diseases from various scans. Neural networks are ideal for recognizing diseases using scans.
Neural networks have been used for building black-box models in geoscience.
Diagnosing the Cardiovascular System
Experimentally, neural networks are used to model the human cardiovascular system. If this is carried out successfully, then potential harmful medical conditions can be detected at an early stage. Thus make the process of combating the disease much easier.
The sense of smell can be an important sense to the surgeon, tele smell would enhance telepresence surgery. Electronic noses have several potential applications in telemedicine. The electronic nose would identify odours in the remote surgical environment. These identified odours would then be electronically transmitted to another site where a door generation system would recreate them.
Neural networks have been used to diagnose cancers, including lung cancer, prostate cancer, colorectal cancer and to distinguish highly invasive cancer cell lines from less invasive lines using only cell shape information.
Neural Networks in business
Neural networks are broadly used in financial operations, enterprise planning, trading, business analytics and product maintenance. Neural networks have also used in business applications such as forecasting and marketing research solutions, fraud detection and risk assessment.
For social media
Neural networks learning algorithms find extensive applications in the world of social media. For example - when you upload any photo to social media, the service automatically highlights faces and prompts friends to tag. In a video highlighting social media’s Artificial Intelligence research, they discuss the applications of Neural Networks to power their facial recognition software.
By making use of the neural network and its learnings, the e-commerce giants are creating Artificial Intelligence systems.
In banking or personal finances
Most large banks are offering the ability to deposit cheques through a smartphone application. They eliminating the need for customers to physically deliver a cheque to the bank. The technologies that power these applications use Neural Networks.
For weather forecasting
Neural nets are involved in the real-time processing of satellite and radar images that not only detect early formation of hurricanes and cyclones but also detect sudden changes in wind speed and direction that indicate a forming tornado.