method of artificial variables

method of artificial variables的基本解释

-

人工变量法

与method of artificial variables相关的网络例句 [注：此内容来源于网络，仅供参考]

Stochastic variables included driven accelerations, driven time, torques, frictions and damps were considered basically. In the first, Monte Carlo method was applied to generate stochastic variables and dynamical responds of mechanism. Secondly, the application of Artificial Neural Network was motivated by the approximate concepts inherent in reliability analysis and time consuming repeated analyses required for MC.

将驱动加速度、驱动时间、摩擦和阻尼力等作为随机变量，应用蒙特卡罗方法，取得动态参数样本，再利用人工神经网络方法，根据抽取的样本对网络进行训练，统计网络输出得到动态应力分布，进而求出机构动态强度可靠度。

We use the filtered variables to build Ridge estimation equation, and calculate the multiple correlation coefficient, at the same time passed the correlation test of the Ridge estimation equation; we built forward neural network model based on SCG method and momentum method under the MATLAB 6.5 situation, when estimating the fuel load of the sampled plots, the average precision of the artificial neural network model is 89.51%.

利用筛选出的自变量构建岭估计方程，并通过了岭估计方程的相关检验；在MATLAB6.5环境下构建基于SCG法和动量法的前向神经网络模型，在对所设置实验样地可燃物估测中人工神经网络模型估测的平均精度为89.5%。

The first part is the introduction, which generally introduces the research purpose and significance of this thesis, the summary of the financial pre-warning researches both home and abroad, and the research main contexts and research methods; The second part is the comparison on the financial pre-warning methods existent, which compares the different methods by categories, makes a further analysis on the limits of existent methods, and proposes the improve thoughts of this research based on that; The third part is the basic theory, which makes a summary of the referent theories exerted on the research, and exposit the comparing mechanism of the grey prediction theory and the artificial neural network method concise; The fourth part is the frame work of the model, which illuminates the research designs step by step, such as the definition of the financial crisis, the method of sample select, the select and definition of the pre-warning variables, and makes an exposition of the establishment procedures of the whole models at last; The fifth part is the financial pre-warning based on the theory of grey prediction and artificial neural network, which mainly demonstrate the model establishment in the concrete, dividing into four part to carry out the part of pragmatic research integrally, building of indexes system, establishment of BP neural networks, dynamic financial pre-warning and test, analysis on the pre-warning result; The sixth part is conclusion, which sums up the main results of the whole research, clarifies the innovative points, and makes a discussion on the limits and future study directions of the research in this thesis.

其中，第一部分为导论，总括性概述本文的研究目的与意义，国内外研究综述，以及本文的研究内容和方法；第二部分为现有财务预警研究方法剖析，通过对现有预警方法进行分类比较，进一步分析现有预警方法的局限性，并在此基础上提出本文研究的改进思路；第三部分基本理论，对本文研究中运用的相关理论进行扼要概述，并简要阐述灰色预测理论与人工神经方法的融合机理；第四部分为模型研究框架，逐步阐释模型对财务困境的界定，样本数据的选取方法，预警变量的选取与定义等各个部分的研究设计，并对整体模型的构建步骤进行简要阐述；第五部分为基于灰色神经网络模型的财务预警，主要论述动态预警模型的具体实现过程，分模型指标体系的建立，BP神经网络的建立，动态财务预警与检验，以及预警结果分析四个部分全面阐述本文实证分析过程；第六部分为结论，总结本文研究得到的主要研究结论，以及本文研究中的创新之处，并对论文的不足与后续发展研究进行探讨。

与method of artificial variables相关的网络解释 [注：此内容来源于网络，仅供参考]

method of artificial variables：人工变量法

method of approximation 近似法 | method of artificial variables 人工变量法 | method of balayage 扫除法