Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Fault detection and isolation schemes are designed to detect the onset of adverse events during operations of complex systems, such as aircraft and industrial processes. The state-of-the-art fault diagnosis systems on aircraft combine an expert-created reference model of the associations beten faults and symptoms, and a Naive Bayes reasoner. For complex systems with many dependencies beten components, the expert-generated reference models are often incomplete, which hinders timely and accurate fault diagnosis. Mining aircraft flight data is a promising approach to finding these missing relations beten symptoms and data. Hover, mining algorithms generate a multitude of relations, and only a small subset of these relations may be useful for improving diagnoser performance. ,  adopt a knowledge engineering approach that combines data mining methods with human expert input to update an existing reference model and improve the overall diagnostic performance.  discuss three case studies to demonstrate the effectiveness of this method.
['Daniel L. C. Mack', 'Gautam Biswas', 'Xenofon D. Koutsoukos', 'Dinkar Mylaraswamy']
I am writing a research paper on a idea Learning Bayesian Network Structures to Augment Aircraft Diagnostic Reference Models
[{"from": "human", "value": "I am writing a research paper on a idea Learning Bayesian Network Structures to Augment Aircraft Diagnostic Reference Models"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Fault detection and isolation schemes are designed to detect the onset of adverse events during operations of complex systems, such as aircraft and industrial processes. The state-of-the-art fault diagnosis systems on aircraft combine an expert-created reference model of the associations beten faults and symptoms, and a Naive Bayes reasoner. For complex systems with many dependencies beten components, the expert-generated reference models are often incomplete, which hinders timely and accurate fault diagnosis. Mining aircraft flight data is a promising approach to finding these missing relations beten symptoms and data. Hover, mining algorithms generate a multitude of relations, and only a small subset of these relations may be useful for improving diagnoser performance. ,  adopt a knowledge engineering approach that combines data mining methods with human expert input to update an existing reference model and improve the overall diagnostic performance.  discuss three case studies to demonstrate the effectiveness of this method."}]