Applications of Neural Network

A neural network is a processing device, either an algorithm or genuine hardware, that endeavors to recognize underlying relationships in a set of data through a process that mimics the way the human brain operates. The computing world has a ton to acquire from neural networks, also known as artificial neural networks or neural nets. The neural networks have the ability to learn by example which makes them very flexible, entirely adaptable, and powerful.
For neural networks, they can adapt to changing input; so the network hence produces the best possible result without redesigning the output criteria. 

The neural networks have a great extent of being utilized in the following areas:

• Air traffic control could be automated with the help of location, elevation, direction, and speed of each radar blip which could be taken as input the network. As a result of this, the output would be the air traffic controller’s instruction which would be a response to each blip.
• Animal behavior, their relationships, and population cycles may be apt for analysis using neural networks.
• Evaluation and valuation of property, buildings, automobiles, machinery, etc. should be an easy task if done with the help of a neural network.
• Wagering on horse races, stock markets, sporting events, etc. could be analyzed with the help of neural network predictions.
• Criminal sentencing could be anticipated using a large sample of crime details as input and the resulting sentences as output.
• Complete physical processes that revolve around various mathematical formulas could be modeled heuristically using a neural network.
• Data mining, cleaning, and validation could be achieved efficiently if we find out which records suspiciously diverge from the pattern of their peers. This could be done with the help of a neural network.
• Direct mail advertisers could use neural network analysis of their databases to decide which customers ought to be focused on, and avoid wasting money on improbable targets.
• Weather prediction may be possible using a neural network. Inputs would include weather reports from surrounding areas. Output(s) could be the future weather in specific areas based on the input information.
• Examination of medical issues is an ideal application for neural networks.
• Research in medical fields relies heavily on classical insights to dissect research data. Therefore, a neural network should be included in the researcher’s tool kit.
• Depth of river water could be predicted based on upstream reports, and the time and location of each report.
• Schedule optimization of buses, airplanes, and elevators could be done efficiently by predicting demand.
• Staff scheduling optimization for restaurants, retail stores, police stations, banks, etc., could be done based on the customer flow, day of the week, paydays, holidays, weather, season, etc.
• Strategy Analysis for games, business, and war can be performed by observing the expert player’s response to given stimuli. For example, a football coach must decide whether to kick, piss or ruin on the last down.