“Neural networks do not perform miracles. But if used sensibly they can produce some amazing results.”
In information technology, a neural network (NN, ANN) is a system of programs and data structures that approximates the operation of the human brain. They are biologically inspired. A neural network usually involves a large number of processors operating in parallel, each with its own small sphere of knowledge and access to data in its local memory. Typically, a neural network is initially "trained" or fed large amounts of data and rules about data relationships.
Networks provide significant benefits in business applications. Neural networks are now globally recognized as the most effective and appropriate artificial intelligence technology for pattern recognition and as a result, they are actively being used for such applications as bankruptcy prediction, predicting costs, forecasting revenue, supporting commercial gaming and processing documents or images electronically. They solve “real world” problems in business and engineering.
In order for neural networks to solve “real world” problems they must be fed information. They require correct data pre processing, correct architecture selection and correct network training. Neural networks have many components (input layers, hidden layer, output layer, connections/arcs, weights, activation functions, training set and learning) and in order for neural networks to be successful they require proper user skills. The user must be familiar with and understand all the components. Most failures in neural networks in the past have come from improper user skills in appropriate preparation of data and design of a neural network. Nowadays, business benefits of neural technology are highly underestimated still due to difficulties in appropriate data pre-processing and network construction.
I have already briefly mentioned some of the benefits of neural networks in the business environment. The question is “Can Neural Networks be useful for business?”
After attending my lectures, studying the lecture slides and after my research I think Neural Networks are extremely useful for businesses and below I have listed why I think this.
After attending my lectures, studying the lecture slides and after my research I think Neural Networks are extremely useful for businesses and below I have listed why I think this.
Detection of medical phenomena
A variety of health-related indices, for example, a combination of heart rate, levels of various substances in the blood, respiration rate can be monitored. The onset of a particular medical condition could be associated with a very complex (e.g., nonlinear and interactive) combination of changes on a subset of the variables being monitored. Neural networks have been used to recognize this predictive pattern so that the appropriate treatment can be prescribed.
Stock market prediction
Here is another example; a complex, multidimensional example of how neural networks are used in reality is in the fluctuations of stock prices and stock indices. In some circumstances, neural networks are being used by many technical analysts to make predictions about stock prices based upon a large number of factors such as past performance of other stocks and various economic indicators.
Credit assessment
‘’Neural networks have extremely powerful predictive capabilities, designed to notice anomalies in spending behaviour which could signal unauthorized card use. Suspicious transactions can be identified as they enter the payment system at the authorization stage, allowing your card issuer to quickly alert you of possible fraud -- often stopping thieves in their tracks.’’ Visa
Monitoring machinery
Neural networks can be beneficial for businesses for cutting costs by bringing additional expertise to scheduling the preventive maintenance of machines. With training, neural networks can distinguish between the sounds a machine makes when it is running normally ("false alarms") compared to when it is on the verge of a problem. After this training period, the expertise of the network can be used to warn a technician of an upcoming breakdown, before it occurs and causes costly unforeseen "downtime”, saving time and money for the business. Time is money!
Engine management
There are many more interesting facts about neural networks. The following are some interesting websites I came upon while doing my research
No comments:
Post a Comment