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Haoying Chen, Yifan Wang and Haibo Zhang
In the overall design process of the turbofan engine, it has become crucial to address the challenge of selecting design parameters that not only meet the flight thrust demand but also enhance engine economy. As the demand for stealth performance in futu...
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Thibaut Théate and Damien Ernst
Classical reinforcement learning (RL) techniques are generally concerned with the design of decision-making policies driven by the maximisation of the expected outcome. Nevertheless, this approach does not take into consideration the potential risk assoc...
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Zhehu Yuan, Yinqi Sun and Dennis Shasha
Database and data structure research can improve machine learning performance in many ways. One way is to design better algorithms on data structures. This paper combines the use of incremental computation as well as sequential and probabilistic filterin...
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Chuan Xie, Weixing Yao, Danfa Zhou and Caijun Xue
The main concern of the paper is the concurrent treatment of size and layout variables in the static?dynamic coupled layout optimization of stiffened plates. As compared to size optimization alone, layout optimization is a more challenging task, and the ...
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Yangjing Wang, Jinquan Huang, Muxuan Pan and Wenxiang Zhou
The variable cycle engine switches working modes by way of changing variable-geometry components to achieve the dual advantages of high unit thrust and low specific fuel consumption. Due to the lack of a large amount of rig test data and the complex mode...
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