๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

Nuclear power plant fault diagnosis based on genetic-RBF neural network

โœ Scribed by Xiao-cheng Shi; Chun-ling Xie; Yuan-hui Wang

Book ID
107512705
Publisher
Harbin Engineering University
Year
2006
Tongue
English
Weight
402 KB
Volume
5
Category
Article
ISSN
1671-9433

No coin nor oath required. For personal study only.

๐Ÿ“œ SIMILAR VOLUMES

A dynamic neural network based accident
A dynamic neural network based accident diagnosis advisory system for nuclear power plants
โœ Seung Jun Lee; Poong Hyun Seong ๐Ÿ“‚ Article ๐Ÿ“… 2005 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 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

A dynamic neural network aggregation mod
A dynamic neural network aggregation model for transient diagnosis in nuclear power plants
โœ Kun Mo; Seung Jun Lee; Poong Hyun Seong ๐Ÿ“‚ Article ๐Ÿ“… 2007 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 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