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Keywords: neural network
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Proceedings Papers

Proc. ASME. ICONE29, Volume 4: SMRs, Advanced Reactors, and Fusion, V004T04A005, August 8–12, 2022
Paper No: ICONE29-90511
... Abstract The methodology of artificial intelligence (AI), particularly artificial neural network (ANN), would be in favor of nuclear energy system development. These ANN simulators may provide more efficient means than the traditional nuclear design codes, especially for the design of the key...
Proceedings Papers

Proc. ASME. ICONE29, Volume 15: Student Paper Competition, V015T16A063, August 8–12, 2022
Paper No: ICONE29-91880
.... In actual operation, it is difficult for classical PID control to ensure a satisfactory control performance. In this paper, the neural network methods are used to optimize the parameters of the PID controller, and a neural network controller is designed. The controller of the system consists of two...
Proceedings Papers

Proc. ASME. ICONE29, Volume 3: I&C, Digital Control, and Influence of Human Factors, V003T03A005, August 8–12, 2022
Paper No: ICONE29-89440
... software error severity, and so on. The rapidly developed neural network technology provides a new kind of research tool to analyze these recorded data. This paper uses software error data to train a Recurrent Neural Network (RNN), the trained RNN can give more correct software reliability growth...
Proceedings Papers

Proc. ASME. ICONE2020, Volume 1: Beyond Design Basis; Codes and Standards; Computational Fluid Dynamics (CFD); Decontamination and Decommissioning; Nuclear Fuel and Engineering; Nuclear Plant Engineering, V001T06A005, August 4–5, 2020
Paper No: ICONE2020-16138
... neural networks (NN) for comparative analysis which can provide advice for follow-up research. In the paper, RCS has been analyzed and typical fault have been analyzed through PCTRAN simulator. On this basis, two kinds of NN combined with fuzzy systems: radial basis function (RBF) and back propagation...
Proceedings Papers

Proc. ASME. ICONE2020, Volume 3: Student Paper Competition; Thermal-Hydraulics; Verification and Validation, V003T12A050, August 4–5, 2020
Paper No: ICONE2020-16900
... detection. The structure of the network packets is analyzed in detail with examples. Then, Features are extracted from network packets. An unsupervised neural network called autoencoder is applied for anomaly detection. Training and testing database are captured from a physical PLC system which simulates...
Proceedings Papers

Proc. ASME. ICONE10, 10th International Conference on Nuclear Engineering, Volume 3, 71-78, April 14–18, 2002
Paper No: ICONE10-22088
... Flow regime identification for an adiabatic vertical co-current downward air-water two-phase flow in the 25.4 mm ID and the 50.8 mm ID round tubes was performed by employing an impedance void meter coupled with the neural network classification approach. This approach minimizes the subjective...