数列预测一直是评价决策中最常见而又难于把握的问题之一。
Data series forecasting is one of the most common problems which are difficult to grasp in evaluation and decision.
本文将灰色预测中的数列预测模型和系统预测模型应用于农村电力网规划中的用电需求预测。
In this paper , two grey prediction models which are applied to long term load forecast in regional power grid planning are discussed.
介绍了灰色系统理论，提出了灰色GM(1,1)数列预测模型，把它应用到干旱灾害预报中，取得了良好效果。
This article gives an introduction to the theory of the grey systems and presents forecasting models of the grey GM (1, 1) sequence. Its appliance in forecasting drought has come into good effect.
同时，运用灰色理论中的等间距数列预测建立了GM（1，1）模型，对膜致应力-时间的关系进行了数据分析。
Meanwhile, through the grey forecasting of equidistant data sequent, GM(1,1) modeling is established, while the data analysis about the relationship between additive stress and time is made.
并采用一个矿山实测得到的震级数列进行了进化神经网络方法的实用性验证，结果表明，进化神经网络不但模型拟合精度高，而且预测性能也较好。
The proposed model is tested by a real magnitude series from a mine, and results show that evolutionary neural network model has not only high precision, but also high prediction.
灰色预测模型为矿井瓦斯涌出量时间动态数列的预测提供了一条新的途径。
The grey prediction model provides a new way for predicting the time dynamic numerical array of mine gas emission rate.
蛋白组学和微数列用来检测西妥昔单抗的分子有效性并且明确生物标记物对疗效的预测方面的作用。
Proteomics and microarrays were used to monitor the molecular response to cetuximab and to identify profiles and biomarkers to predict treatment efficacy.
课程期间我们将检视数种学习技巧在一些领域上的应用如电脑视觉、电脑绘图、数据库搜索和时间数列分析与预测。
During this course we will examine applications of several learning techniques in areas such as computer vision, computer graphics, database search and time-series analysis and prediction.
灰色预测是灰色理论的主要内容之一，其中数列灰预测是灰色预测的主要类型之一。
Grey prediction is one of the main ideas of grey theory. The sequence grey prediction is one of major type of grey prediction.
利用“数列灰预测”建立了管道腐蚀预测的新模型，介绍了三种常用的数据处理方式。
We used Array Grey Prediction method found a new model to predict pipeline's corrosion trend and introduce three typical data processing mode.
为精确地预测电量，利用灰色系统的理论，对石家庄市网已有年用电量的离乱数列进行数据处理；
To precisely predict the electricity demand, existing annual demand data of Shijiazhuang urban network were processed by using grey system theory.
我们也将在课程期间检视数种学习技巧在一些领域上的应用如电脑视觉、电脑绘图、数据库搜索和时间数列分析与预测。
During the course we will examine applications of several learning techniques in areas such as computer vision, computer graphics, database search and time-series analysis and prediction.
我们也将在课程期间检视数种学习技巧在一些领域上的应用如电脑视觉、电脑绘图、数据库搜索和时间数列分析与预测。
During the course we will examine applications of several learning techniques in areas such as computer vision, computer graphics, database search and time-series analysis and prediction.
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