查询词典 forecasting

Quantitative methods, along with qualitative methods were used to analyze the effect of collaborative forecasting on supply chain performance on the condition of E-Business.

本文在电子商务和协同计划预测补给策略CPFR(Collaborative Planning， Forecasting and Replenishment)的框架下，采用了定量和定性相结合的方法研究了供应链成员联合预测需求对系统成本的影响。

Among used machine learning methods, the gradient descent method is widely used to train various classifiers, such as Back-propagation neural network and linear text classifier. However, the gradient descent method is easily trapped into a local minimum and slowly converges. Thus, this study presents a gradient forecasting search method based on prediction methods to enhance the performance of the gradient descent method in order to develop a more efficient and precise machine learning method for Web mining.However, a prediction method with few sample data items and precise forecasting ability is a key issue to the gradient forecasting search method. Applying statistic-based prediction methods to implement GFSM is unsuitable because they require a large number of data items to model a prediction model. In the contrast with statistic-based prediction methods, GM(1,1) grey prediction model does not need a large number of data items to build a prediction model, and it has low computational load. However, the original GM(1,1) grey prediction model uses a mathematical hypothesis and approximation to transform a continuous differential equation into a discrete difference equation in order to model a forecasting model.

其中梯度法是一个最常被使用来实现机器学习的方法之一，然而梯度法具有学习速度慢以及容易陷入局部最佳解的缺点，因此，本研究提出一个梯度预测搜寻法则(gradient forecasting search method， GFSM)来改善传统梯度法的缺点，用来提升一些以梯度学习法则为基础的分类器在资讯探勘上的效率与正确性；而一个所需资料量少、计算复杂度低且精确的预测模型是梯度预测搜寻法能否有效进行最佳解搜寻之关键因素，传统统计为基础之预测方法的缺点是需要较大量的数据进行预测，因此计算复杂度高，灰色预测模型具有建模资料少且计算复杂度低等优点，然而灰色预测理论以连续之微分方程式为基础，并且透过一些数学上的假设与近似，将连续之微分方程式转换成离散之差分方程式来对离散型资料进行建模及预测，这样的作法不尽合理，且缺乏数学理论上的完备性，因为在转换过程中已经造成建模上的误差，且建模过程仅考虑相邻的两个资料点关系，无法正确反应数列未来的变化趋势。

This paper introduces the significance of the interactive correct technology applied to forecasting hydrograph, and the process-fit-smoothness and the cubic interpolation technology. Based on the technology above, it can be realized to correct the forecasting hydrograph interactively in the form of elastic which is applied to the flood forecasting system.

分析了水文预报过程交互式修正技术在洪水预报工作中的重要性，介绍了过程拟合平滑技术和样条插值技术，基于此基础上研究实现了以橡皮筋形式交互式修正水文预报过程的技术，并应用于洪水预报系统中。

According to the features of load forecasting of small region,a decoupling mechanism based error analysis model and corresponding forecasting mechanism are proposed in which the short-term load forecasting is divided into two parts,namely load level forecasting and per unit curve forecasting.

针对小地区短期负荷预测的特点，提出了基于解耦机制的误差分析模型和预测机制，将短期负荷预测分为负荷水平预测和标幺曲线预测两部分。

Based on AFCT, a new adaptive staring principle is established using floating threshold which is calculated by system reference model based on extrapolation method and linear regression algorithm. The principle of "forecasting model on line identifier"and"forecasting model parameters'selftuner"are put forward. In the module of"adjustment mechanism", the forecasting method of break points is introduced to fulfill control functions to "forecasting model parameters'self tuner".

本文详细讨论了针对输电线路主保护的自适应预测模型的建立方法，应用时间序列法和自回归模型或动平均自回归模型建立了精确反映保护对象状态量的系统预测模型，以自回归模型为例给出了"预测模型在线辨识"环节和"模型参数自适应校正"环节的算法，应用"适应机构"实现其对"模型参数自适应校正"环节的控制作用，应用并行计算算法实现了在继电保护中的"预测模型在线辨识"环节，使系统状态预测模型自适应于变化的电力系统。

The concept and the classification of forecasting are addressed. Aiming at the disadvantages of the current forecasting models, such as requirement for more data and narrow application extent, an improved GM(1,1)-transfer function-noise model for forecasting is proposed. In the first stage, the GM(1,1) model improving the generation method of neighborhood system is adopted so as to fulfil the forecasting by only using a few of data.

介绍了预测的概念与分类；针对现有产品回收预测模型数据需求量大和适用范围窄的不足，提出了改进GM(1，1)/传递函数噪声两阶段预测模型；产品回收初期数据缺乏，主要采用改进了邻域系生成方法的IGM(1，1)模型，从而实现少量数据情况下的准确预测。

Conventionally the electric load forecasting can hardly attain a result whose accuracy meets what's required. A short-term load forecasting model is therefore developed to solve the problem, based on the process neural network of which the input is the function of time and the high forecasting accuracy is available. Describes the structure of the model, discrete data fitting method by the expansion of function orthogonal basis and learning algorithm.

针对目前常用方法在解决负荷预测问题时，结果往往难以达到工程要求精度的现状，利用过程神经网络输入为时间函数以及预测精度高的特点，建立了基于过程神经网络的电力系统短期负荷预测模型；给出了模型的结构，基于函数正交基展开的离散数据拟合方法以及模型的学习算法。

By study of the statistic characteristics of flood forecasting errors and their confidence intervals for Nushi watershed at Sanhuajian of the Yellow River and on the basis of a comparison of the precision criterion currently used for flood forecasting with the result of the error confidence interval method, it is concluded that the error of flood forecasting is of the characteristic of skew probability distribution, and that the evaluated results of forecasting errors are different by the above two methods.

因此，本文在三花间伊河卢氏流域洪水预报的基础上研究了误差置信限及误差置信限评定方法，并将误差置信限评定结果与现行水情预报精度标准[1]评定结果进行了比较。1 现行洪水预报评定方法流域洪水预报精度评定内容包括洪峰流量、峰现时间和洪量等。洪水预报误差指标有绝对误差、相对误差和确定性系数3种。预报误差小于许可误差时为合格预报。

The paper summarizes theories and practices concerning data mining at the beginning. According to actual conditions of data forecasting, the paper particularizes two basic tasks in data mining, namely, exploring data analysis and forecasting modeling for classification, and employs them in load forecasting practically. Then a special short-term load-forecasting arithmetic is forwarded based on the former work, which can efficiently take into account weather effects on the load, and hence improve the accuracy of load forecasting.

本文概述了数据挖掘技术的有关内容；并针对负荷预测的实际情况，详细介绍了数据挖掘中的两个基本任务：探索性数据分析和用于分类的预测建模，并将其运用于负荷预测之中；根据所得结果提出了一种基于数据挖掘的短期负荷预测算法，该算法能够有效的考虑气象因素对负荷的影响，从而提高了负荷预测的精度。

So this paper applied Grey forecasting GM (1,1) model and its generated models, the Grey Markov numerical forecasting model and Comprehension model, to develop a net interest margin change forecasting model, a net interest margin forecasting model, a new decision model concerned with commercial bank interest-sensitive assets portfolio and a new expected return decision model of interest-sensitive assets portfolio.

本文以灰预测GM(1，1)模式，以及其衍生之灰马可夫预测模式与内涵模式，构建新的净利息边际变动率预测模式、净利息边际金额预测模式、利率敏感性资产投资组合最适配置决策模式与利率敏感性资产投资组合最适配置预期报酬率决策模式等利率敏感性缺口管理预测模式。

In the negative and interrogative forms, of course, this is identical to the non-emphatic forms.

。但是，在否定句或疑问句里，这种带有"do"的方法表达的效果却没有什么强调的意思。

Go down on one's knees;kneel down

屈膝跪下。。。下跪祈祷