Intelligent Adaptive Systems for Real World Applications
Intelligent adaptive systems learn from data to improve their performance on a task as they gain experience on the task. They may incorporate machine learning and pattern recognition techniques such as neural networks.
Machine learning and pattern recognition systems need data:
If your organisation already has data, consider what information could be revealed by the data or what application the data could be used for?
If your organisation does not have data then consider if perhaps it is already generated dynamically by some process within your organisation or otherwise could either be collected or generated for future use?
Data could come from multiple sources and be fused to provide solutions and applications not otherwise thought of.
For best results the data should be a balanced representation of the application domain.
One approach to identifying applications in your organisation is to ask if there are any existing systems with poor performance that could be improved by machine learning and pattern recognition techniques?
The following benefits and examples may help:
Optimise material use
Machine health monitoring
Contact KWiSystems explaining what data you have or could collect or generate and what results or information you would like to obtain from the data.