Methods and Procedures for the Verification and Validation of Artificial Neural Networks

• Κύριος συγγραφέας: Taylor, Brian J. (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Boston, MA : Springer US, 2006.
• Θέματα: Computer science.; Computer organization.; Computer communication systems.; User interfaces (Computer systems).; Artificial intelligence.; Computer graphics.; Pattern recognition.; Computer Science.; Artificial Intelligence (incl. Robotics).; Computer Communication Networks.; User Interfaces and Human Computer Interaction.; Computer Systems Organization and Communication Networks.; Computer Imaging, Vision, Pattern Recognition and Graphics.; Pattern Recognition.

Artificial neural networks are a form of artificial intelligence that have the capability of learning, growing, and adapting with dynamic environments. With the ability to learn and adapt, artificial neural networks introduce new potential solutions and approaches to some of the more challenging pro...

Πίνακας περιεχομένων:

• Background of the Verification and Validation of Neural Networks
• Augmentation of Current Verification and Validation Practices
• Risk and Hazard Analysis for Neural Network Systems
• Validation of Neural Networks Via Taxonomic Evaluation
• Stability Properties of Neural Networks
• Neural Network Verification
• Neural Network Visualization Techniques
• Rule Extraction as a Formal Method
• Automated Test Generation for Testing Neural Network Systems
• Run-Time Assessment of Neural Network Control Systems.