𝔖 Bobbio Scriptorium
✦   LIBER   ✦

A dynamic neural network aggregation model for transient diagnosis in nuclear power plants

✍ Scribed by Kun Mo; Seung Jun Lee; Poong Hyun Seong

Book ID
104087703
Publisher
Elsevier Science
Year
2007
Tongue
English
Weight
720 KB
Volume
49
Category
Article
ISSN
0149-1970

No coin nor oath required. For personal study only.

πŸ“œ SIMILAR VOLUMES

A dynamic neural network aggregation mod
A dynamic neural network aggregation model for transient diagnosis in nuclear power plants
✍ Kun Mo; Seung Jun Lee; Poong Hyun Seong πŸ“‚ Article πŸ“… 2007 πŸ› Elsevier Science 🌐 English βš– 720 KB

A dynamic neural network aggregation (DNNA) model was proposed for transient detection, classification and prediction in nuclear power plants. Artificial neural networks (ANNs) have been widely used for surveillance, diagnosis and operation of nuclear power plants and their components. Most studies

A dynamic neural network based accident
A dynamic neural network based accident diagnosis advisory system for nuclear power plants
✍ Seung Jun Lee; Poong Hyun Seong πŸ“‚ Article πŸ“… 2005 πŸ› Elsevier Science 🌐 English βš– 980 KB

In this work, an accident diagnosis advisory system (ADAS) using neural networks is developed. In order to help the plant operators quickly identify the problem, perform diagnosis and initiate recovery actions ensuring the safety of the plant, many operator support systems and accident diagnosis sys