Knowledge-based turbomachinery design system via a deep neural network and multi-output Gaussian process-Reference-Cited by-同舟云学术

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Knowledge-based turbomachinery design system via a deep neural network and multi-output Gaussian process

Published:2022-09 Issue: Volume:252 Page:109352
ISSN:0950-7051
Container-title:Knowledge-Based Systems
language:en
Short-container-title:Knowledge-Based Systems

Author:

Chen Junfeng,Liu Changxing,Xuan Liming,Zhang Zhenwei,Zou Zhengping

Funder

National Major Science and Technology Projects of China

Beihang University

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Management Information Systems,Software

Reference66 articles.

1. Thermoeconomic impact on combined cycle performance of advanced blade cooling systems;Ghigliazza;Appl. Energy,2009

2. Prospects for aero gas-turbine diagnostics: a review;Marinai;Appl. Energy,2004

3. A new approach for enhancing performance of a gas turbine (case study: Khangiran refinery);Farzaneh-Gord;Appl. Energy,2009

4. Development of supercritical CO2 turbomachinery off-design model using 1D mean-line method and deep neural network;Son;Appl. Energy,2020

5. Loss Mechanisms in Turbomachines (Vol. 78897);Denton,1993

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