Applying the hopfield neural network to the solution of the temperature distribution field in heat conduction problems

Deng S; Hwang Y

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Applying the hopfield neural network to the solution of the temperature distribution field in heat conduction problems

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

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This article employs the continuous-time analog Hopfield neural network (CHNN) to compute the temperature distribution in one- and two-dimensional transient heat conduction problems. The relationship between the CHNN synaptic connection weights and the governing equations of the problems is established and a corresponding network connectivity circuit design scheme proposed. The CHNN algorithm is initially applied to the solution of conventional problems and is then used to solve more complicated problems involving time-varying heat flux profiles. The results confirm that the CHNN scheme provides an accurate means of solving the transient temperature distributions of heat conduction problems on a real-time basis.

机译：本文采用连续时间模拟Hopfield神经网络（CHNN）来计算一维和二维瞬态热传导问题中的温度分布。建立了CHNN突触连接权重与问题的控制方程之间的关系，并提出了相应的网络连接电路设计方案。 CHNN算法最初用于解决常规问题，然后用于解决涉及时变热通量曲线的更复杂的问题。结果证实，CHNN方案提供了一种实时解决导热问题瞬态温度分布的准确方法。

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《Numerical Heat Transfer, Part B. Fundamentals: An International Journal of Computation and Methodology》 |2006年第6期|共25页
作者
Deng S; Hwang Y;
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正文语种 eng
中图分类热力工程、热机;
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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. Evaluation of applying axial variation of enrichment distribution method and radial variation of enrichment distribution in WER/1000 reactor using a Hopfield neural network to optimize fuel management [J] . Shima Tayefi, Ali Pazirandeh Progress in Nuclear Energy . 2013,第apra期

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3. Using Hopfield neural network to optimize fuel rod loading patterns in WER/1000 reactor by applying axial variation of enrichment distribution [J] . Shima Tayefi, Ali Pazirandeh Applied Soft Computing . 2014,第Null期

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7. Applying neural networks to the solution of forward and inverse heat conduction problems [O] . S. Deng, Y. Hwang 2006

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8. Scheduling Link Activation in Multihop Radio Networks by Means of Hopfield NeuralNetwork Techniques [R] . Barnhart, C. M., Wieselthier, J. E., Ephremides, A. 1991

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Applying the hopfield neural network to the solution of the temperature distribution field in heat conduction problems

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