查询词典 prediction theory

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。

This method adopts data-based optimization algorithm to design the initial prediction operator and update operator at each decomposition scale, the initial prediction operator and update operator are interpolated with zero, and then the redundant prediction operator and redundant update operator are obtained.

该方法采用基于数据的优化算法，设计每层小波分解的初始预测器和更新器，然后通过对初始预测器和更新器进行插值补零运算，来获得冗余预测器和更新器。

The effective prediction space concept is established, On the base of these, this paper deduces two representations' evaluating equation, one evaluates the prediction error and the other evaluates the prediction error in limited space. First, the error transfer characteristic among subsystems at different space locations is analyzed, and the direct transfer characteristic from discrete standard measure space to the workpiece measure space under measured in measure system is proven. Second, the error reconstruction condition and method of mapping from discrete standard measurement system to continuous standard measurespace are analyzed.

分析了不同空间位置子系统间的误差传递特性，证明了在测量系统中离散标准量值空间向被测量工件量值空间的直接传递性；分析了离散标准量系统向连续量值空间映射的误差重构条件和方法；基于测量样本的有限距离的平稳性，证明了预报模型对动态测量误差的有限收敛性和预报误差的可测度性，进而证明了以离散标准量值系统对被测工件预报修正的可行性和合理性。

And particularly is the discriminatory analysis and Markovian model, their accurate rate of return are more higher than their prediction, this show that their prediction resolutions are unsteady and they have good application value in the prediction of wheat midge.

尤其是判别分析预测法和马尔柯夫链预测法，这两种预测方法的预测准确率和回测准确率相差较大，说明预测效果不稳定，对小麦吸浆虫的预测实际应用价值不大。

The results indicate that the ANN structure and the training sample have some impact on the prediction precision. The real time measured power as input will improve the precision of 30 min ahead prediction, however will decrease the precision of 1h ahead prediction. The results which using the atmospheric data at all different heights as input have a higher accuracy when compared with the results using hub height data only. The designed ANN can forecast the error band.

研究结果表明，神经网络的结构和输入样本对预测结果有一定的影响；实测功率数据作为输入可以提高提前量为30 min的预测精度，而对提前量为1 h的预测精度会降低；把不同高度的数据都作为神经网络的输入比只采用轮毂高度数据的预测精度高；设计的神经网络能够对误差带进行预测。

Owing to the test of fatigue life,possesses a rather big difficulty and its testing data have the characteristics of strong scatterence and if a prediction is made from using grey-forecasting model GM(1,1,thus its prediction value would get a rather big error compared with the real result,This paper hereby put forward a kind of new method to simulate the test.let the data be firstly processed into logarithmic series so as to reduce the scatterence of data,and then carry out the prediction by the use of grey-forecasting model.

由于疲劳寿命试验具有难度较大，其实验数据具有分散性强的特点，如果直接用灰色预测模型（GM（1，1））作预测，其预测值与真实结果的误差较大。在此提出一种试验仿真的新方法。首先将数据处理成对数序列，以降低其数据分散性；然后再用灰色预测模型进行预测。

The statistical simulation analysis method is effective to deal with space- time heterogeneity of earthquakes and risk regions, after 105 count of the va lues of simulating random prediction probability have been got, the objective result s have been got by comparing between the simulation prediction average probabili ty and the practice prediction average probability.

由于统计模拟的方法有效地处理了地震和危险区的时空不均匀性，并且得到经运算105次的统计模拟随机预报概率，将其与实际预报平均概率比较，得到较为客观的结果。

In recent year, it alse is applied in the prediction of plant disease and pest, but there are still no reports on wheat midge prediction. In this paper, ANN was applied in the prediction of wheat midge.

它主要用于模式识别和图像处理，预测和管理等方面，近年来也逐渐开始应用于病虫害预测预报，但在小麦吸浆虫的预测预报却未见报道。

On the basis of the data obtained from the cam-type plastometer, four prediction models including the BP, Elman, RBF and GRNN neural network prediction models were established, which corresponded to the relationship between the deformation stress of nickel-chrome steel with chemistry elements, temperature, strain rate and deformation strain of the steel respectively. A comparative analysis for the prediction accuracy of the four models was obtained.

以凸轮式高速形变试验机进行的热模拟压缩实验得到的实验数据为基础，建立了热轧铬镍钢的变形阻力与其化学成分、变形温度、变形速度及变形程度对应关系的BP、Elman、RBF和GRNN 4种神经网络预测模型；并对4种网络的训练过程和预测精度进行比较分析。

The main methods applied in the thesis are: a trend of potato"s Late Blight of BP neural network long-term prediction model and Grey-Disaster prediction model are constructed with history data, and short-term prediction is constructed with the agriculture experts" experience.

本论文的研究方法是：借助于农业、植保专家经验建立了短期预测，同时通过历史数据建立了晚疫病流行程度的神经网络长期预测模型及灰色灾变模型。

"Please accept this talisman as a token of our thanks."

请收下这个护身符以表达我们的感谢。

If I have that magic, I will be more acceptable in the society.

如果我拥有那种魔法，我将更加被这个社会所容纳。