Asset Details
Do you wish to reserve the book?
Automatic Modeling Method Based on Bayesian Network
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Automatic Modeling Method Based on Bayesian Network
Do you wish to request the book?
Automatic Modeling Method Based on Bayesian Network
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
Automatic Modeling Method Based on Bayesian Network
2020
Overview
In fact, the relationship between fault and test is uncertain, and the traditional testability model cannot deal with uncertain information. Bayesian network model with uncertain information reasoning ability and self-learning ability has become a research hotspot. Aiming at the difficulty and high cost of Bayesian network testability model, a automatic modeling method based on Bayesian network was proposed. This method uses the circuit functional structure relationship characterized by EDA to provide the required conditions for the K2 algorithm, and verifies the results of the structure and parameter learning. Through this method, the Bayesian network model can continuously update the model structure and parameters by combining expert knowledge, historical experience and later use data, making the model more and more accurate. After simulation and comparison, the algorithm can effectively build a model and reduce the workload of related personnel.
Publisher
IOP Publishing
Subject
