人工神经网络在岩石变形温度估算中的应用
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THE Application of Artificial Neural Network to the Estimation of Rock Deformation Temperature
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    摘要:

    Christie (1962)、Smith (1972)和张诩钧(1985)都提出了钠质斜长石的△131- 131(或σ)、 An与温度T的关系图,后来又提出了钠质斜长石变形温度的计算公式。但由于图解的 不便之处及目前应用的公式中推断分界点的不确定性和σ、An与T之间存在一种非线性关系的特 点,本文基于具有高度非线性映射能力的人工神经网络,提出了求解岩石变形温度的新方法。文中先介绍T变形温度计的研究概况,然后阐述了ANN (Artificial Neural Network模型,最后应甩该模型估算岩石变形时的温度,经对比得出,利用人工神经网络在岩石变形温度估算中具有良好的应用效果。

    Abstract:

    Diagrams showing relationship of the temperature (T), An and △131一131 (OR σ)of sodic plagioclase were advanced in succession by Christie (1962), Smith(1972) and Zhang Yijun(1985). Later, the formulae for deformation temperature of sodic plagioclase were put forward by Zhang Yijun. Nevertheless, in view of the inconvenience of the diagram, the uncertainty of the dividing point in the formulae and the nonlinear relationship amongσ,An and T, we present a new method for calculating the temperature of the deformation-artificial neural network,which has accurate nonlinear projection.In this paper, an account is first given about the study of the deformation thermometer,followed by a description of the ANN (Artificial Neural Network) model. With this model, the temperature of the deformation is estimated. A comparison shows that the artificial neural network is very effective in the estimation of the deformation temperature.

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李三忠,朱晓军, 1995. 人工神经网络在岩石变形温度估算中的应用[J]. 岩石矿物学杂志, 14(3):219~225.
, 1995. THE Application of Artificial Neural Network to the Estimation of Rock Deformation Temperature[J]. Acta Petrologica et Mineralogica, 14(3): 219~225.

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