A powerful emerging technology can be used to efficiently process information to achieve greater knowledge and improved decision making. This technology is the field of artificial neural networks, commonly referred to as simply neural networks. Neural networks self-adapt to learn from information, providing powerful models representing knowledge about a specific problem. Origins of Neural Networks Artificial neural networks are the result of academic investigations that involve using mathematical formulations to model nervous system operations. The resulting techniques are being successfully applied in a variety of everyday business applications.
Neural networks represent a meaningfully different approach to using computers in the workplace.
A neural network is used to learn patterns and relationships in data. The data may be the results of a market research effort, the results of a production process given varying operational conditions, or the decisions of a loan officer given a set of loan applications. Regardless of the specifics involved, applying a neural network is a substantial departure from traditional approaches. Neural networks do not require the explicit coding of the problem. For example, to generate a model that performs a sales forecast, a neural network only needs to be given raw data related to the problem.