Applications Neural Networks

Can Neural Networks be useful for Business?
“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.

Source: Integrated Systems

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