Applying neural networks to the solution of forward and inverse heat conduction problems

S. Deng; Y. Hwang

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Applying neural networks to the solution of forward and inverse heat conduction problems

机译：将神经网络应用于正向和反向导热问题的求解

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摘要

This paper employs the continuous-time analogue Hopfield neural network to compute the temperature distribution in forward heat conduction problems and solves inverse heat conduction problems by using a back propagation neural (BPN) network to identify the unknown boundary conditions. The weak generalization capacity of BPN networks is improved by employing the Bayesian regulariza-tion algorithm. The feasibility of the proposed method is examined in a series of numerical simulations. The results show that the proposed neural network analysis method successfully solves forward heat conduction problems and is capable of predicting the unknown parameters in inverse problems with an acceptable error.

机译：本文使用连续时间模拟Hopfield神经网络来计算正向导热问题中的温度分布，并通过使用反向传播神经（BPN）网络来识别未知边界条件来解决逆导热问题。通过使用贝叶斯正则化算法可以改善BPN网络的弱泛化能力。在一系列数值模拟中检验了该方法的可行性。结果表明，所提出的神经网络分析方法成功地解决了前向热传导问题，并能够以可接受的误差预测逆问题中的未知参数。

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《International Journal of Heat and Mass Transfer》 |2006年第26期|p.4732-4750|共19页
作者
S. Deng; Y. Hwang;
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作者单位

Department of Weapon System Engineering, Chung Cheng Institute of Technology, National Defense University, No. 190, Sanyuan 1st St., Dashi Jen, Taoyuan 33509, Taiwan, ROC;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种 eng
中图分类热力工程理论;热学;
关键词
neural network; inverse heat conduction problems (IHCPs);

机译：神经网络;逆热传导问题（IHCP）;

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专利

1. Applying the hopfield neural network to the solution of the temperature distribution field in heat conduction problems [J] . Deng S, Hwang Y Numerical Heat Transfer, Part B. Fundamentals: An International Journal of Computation and Methodology . 2006,第6期

机译：将Hopfield神经网络应用于热传导问题中温度分布场的求解
2. On-line heat flux estimation of a nonlinear heat conduction system with complex geometry using a sequential inverse method and artificial neural network [J] . Huang Shuwen, Tao Bo, Li Jindang, International Journal of Heat and Mass Transfer . 2019,第NOVa期

机译：基于顺序逆方法和人工神经网络的复杂几何非线性导热系统在线热通量估算
3. On-line heat flux estimation of a nonlinear heat conduction system with complex geometry using a sequential inverse method and artificial neural network [J] . Huang Shuwen, Tao Bo, Li Jindang, International Journal of Heat and Mass Transfer . 2019,第Nova期

机译：基于顺序逆方法和人工神经网络的复杂几何非线性导热系统在线热通量估计
4. A Surrogate Forward Model Using Artificial Neural Networks in Conjunction with Bayesian Computations for 3D Conduction-Convection Heat Transfer Problem [C] . M. K. Harsha Kumar, P. S. Vishweshwara, N. Gnanasekaran International Conference on Soft Computing for Problem Solving . 2020

机译：使用人工神经网络与贝叶斯计算的三维传导传热问题相结合的代理前进模型
5. Real-time heat flux estimation using filter based solutions for inverse heat conduction problems [D] . Najafi, Hamidreza. 2015

机译：使用基于滤波器的解决方案实时求解逆热传导问题的热通量
6. A neural network model for development of reaching and pointing based on the interaction of forward and inverse transformations [O] . Naohiro Takemura, Toshio Inui, Takao Fukui -1

机译：基于正反变换交互作用的到达和指向发展神经网络模型
7. Applying neural networks to the solution of forward and inverse heat conduction problems [O] . S. Deng, Y. Hwang 2006

机译：将神经网络应用于正向和反向导热问题的求解

Applying neural networks to the solution of forward and inverse heat conduction problems

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