Nuclear Power Plant Status Diagnostics Using an Artificial Neural Network-Reference-Cited by-同舟云学术

Nuclear Power Plant Status Diagnostics Using an Artificial Neural Network

Published:1992-03 Issue:3 Volume:97 Page:272-281
ISSN:0029-5450
Container-title:Nuclear Technology
language:en
Short-container-title:Nuclear Technology

Author:

Bartlett Eric B.¹,Uhrig Robert E.¹

Affiliation:

1. University of Tennessee–Knoxville, Department of Nuclear Engineering Knoxville, Tennessee 37996-2300

Publisher

Informa UK Limited

Subject

Condensed Matter Physics,Nuclear Energy and Engineering,Nuclear and High Energy Physics

Link

https://www.tandfonline.com/doi/pdf/10.13182/NT92-A34635

Reference6 articles.

1. E. B. BARTLETT, “Nuclear Power Plant Status Diagnostics Using Simulated Condensation: An Auto-Adaptive Computer Learning Technique,” PhD Dissertation, University of Tennessee-Knoxville (1990).

2. Parallel Distributed Processing

3. Stochastic Simulation

4. “Watts Bar Malfunction Cause and Effects Report,” Tennessee Valley Authority (1989).

Cited by 122 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Event diagnosis method for a nuclear power plant using meta-learning;Nuclear Engineering and Technology;2024-01

2. Application of deep learning techniques for nuclear power plant transient identification;Annals of Nuclear Energy;2023-12

3. Adaptive neural network sliding mode controller design for load following of nuclear power plant;Progress in Nuclear Energy;2023-12

4. Artificial Intelligence in Physical Science;Marvels of Artificial and Computational Intelligence in Life Sciences;2023-09-18

5. Probabilistic monitoring of nuclear plants using R-vine copula;Annals of Nuclear Energy;2023-09