What kind of real-world problems can neural networks solve?
A. Neural networks can be applied to almost any problem where you have 1) historical data and 2) a need to create a model for that data. Neural networks have been successfully applied to broad spectrum of data-intensive applications, such as: • Process Modeling and Control – Creating a neural network model for a physical plant then using that model to determine the best control settings for the plant. • Machine Diagnostics – Detect when a machine has failed so that the system can automatically shut down the machine when this occurs. • Portfolio Management – Allocate the assets in a portfolio in a way that maximizes return and minimizes risk. • Target Recognition – Military application which uses video and/or infrared image data to determine if an enemy target is present. • Medical Diagnosis – Assisting doctors with their diagnosis by analyzing the reported symptoms and/or image data such as MRIs or X-rays. • Credit Rating – Automatically assigning a company’s or individuals credit rati
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