time series vector
英 [taɪm ˈsɪəriːz ˈvektə(r)]
美 [taɪm ˈsɪriːz ˈvektər]
网络 时间序列向量
双语例句
- The embedded ts() function creates a time series object out of the vector glarp$ livingroom.
嵌入的ts（）函数通过向量glarp$livingroom创建一个时间序列对象。 - In time series analysis of rock burst, the rock burst is seen as a time series process, and the nonlinear relationship between time series is built using support vector machine ( SVM).
针对这一问题，将冲击地压看作一时间序列过程，采用支持向量机建立冲击地压序列之间的非线性关系； - Calculation Lyapunov exponent spectrum of time series based on least-squared support vector machine Within the assigned period of time, the number of successful grasping of the glider will be counted.
采用LS-SVM计算时间序列的Lyapunov指数谱于指定时间内数算成功接回滑翔机的次数。 - Time Series Forecast of Rotor Vibration Based on Support Vector Autoregressive
基于SVAR的汽轮机转子振动时间序列预测 - The Prediction of Financial Time Series Based on Support Vector Machine
基于支持向量机的金融时间序列预测 - Prediction of gas concentration chaotic time series based on support vector machines
基于SVM的瓦斯体积分数混沌时间序列预测 - Experiments on nonlinear time series prediction with least square support vector regression machine
最小二乘回归支持向量机对非线性时间序列预测的试验分析 - For multiple stationary time series Granger causality tests and vector autoregressive models are presented.
多平稳时间序列，“格兰其”成员因果律测试和自回归模式给的矢量。 - Research on Time Series Based on Support Vector Regression Model for Deformation Observation
基于时间序列支持向量回归模型的变形监测研究 - Research on the Prediction of the Chaotic Time Series Based on Lease Square Support Vector Machine
基于最小二乘支持向量回归的混沌时间序列预测研究 - Study on Wind Speed Forecasting of Wind Farm Based on Time Series and Support Vector Machine
基于时间序列与支持向量机的风电场风速预测研究 - Predicting Chaotic Time Series Using Support Vector Machines Optimized by Genetic Algorithm
GA优化支持向量机用于混沌时间序列预测 - This paper uses such time series analysis methods as Cointegration and Vector Autoregression model based Granger Cause Test and anticipation Variance Decomposition to analyze the influence on stock market by credit channel. The result shows that credit channel has an apparent negative influence on China's stock market.
本文运用协整与基于向量自回归模型的格兰杰因果检验和预测方差分解等时间序列分析方法，实证分析信贷渠道对股票市场的影响，结果表明信贷渠道对我国股票市场产生显著的负相关影响。 - The corresponding model of realized covariance matrix of in this paper vector high-frequency financial time series is brought forward and the realized vector autoregressive model is set up is this paper.
对向量高频时间序列的已实现协方差阵提出相应的模型并建立了已实现向量自回归模型。 - To detect scanning network worm attack, failed connection flow ( FCT) time series is established based on characteristics of worm attack, and a novel approach for worm detection based on energy features of FCT time series and support vector machine ( SVM) is proposed.
根据网络蠕虫攻击的特点，建立了能够反映蠕虫扫描特征的失败连接流量（FCT）时间序列，提出了一种基于FCT时间序列小波包能量特征和支持向量机（SVM）的蠕虫检测新方法。 - The analysis results from the simulated and practical signals demonstrate that the end effects of Hilbert-Huang transform could be resolved effectively by the time series forecasting method based on support vector regression machines which is superior to the time series forecasting method based on neural networks.
对仿真和实际信号的分析结果表明，基于支持矢量回归机的数据序列延拓方法能有效地解决Hilbert-Huang变换中存在的端点效应问题，而且其效果优于基于神经网络的数据序列延拓方法。 - With this as the basis, the prediction model of chaos time series is built by using support vector machine from statistic learning theory.
在此基础上利用基于统计学习理论的支持向量机建立混沌时间序列的预测模型。 - The Classification of Time Series Employing Feature Vector and Binary Tree
时间序列基于特征向量的分类与二叉树分类 - On the study of intelligent transportation systems, it puts forward the traffic flow time series prediction based on least squares support vector machines ( LS-SVM), and gives its computational algorithm.
针对城市交通“智能运输系统”，本文提出了基于最小二乘支持向量机（LS-SVM）方法的交通流量时间序列预测，并给出了基于最小二乘支持向量机方法的算法。 - The first step is time series symbolization and the second is structure vector ( SV) model. Sequence pat-tern mining is based on time series symbolization, which segments the time series into sub-series and labels them.
建立结构向量模型。针对时间序列的挖掘通常首先需要将时间序列分段并转变为种类有限的符号序列，以利于进一步进行时间序列模式挖掘。 - A time-delay vector variance method which adopts the time series time-delaying and phase space reconstruction for detecting nonlinearity of time series is introduced. The time-delay vector variance method is proposed to detect nonlinearity and classification of machinery fault signal.
提出了利用时间序列的延时相空间重构，采用延时矢量方差及替代数据的时间序列非线性的检验方法，并将该方法应用于设备故障信号的非线性检验与故障识别。 - Elevator traffic flow has the characteristics of nonlinearity time series and small sample size. Support vector machine is applied to predict elevator traffic flow of time series.
电梯的时间序列交通流数据具有非线性和小样本的特征，利用最小支持向量机技术进行电梯交通流数据预测。 - And then we analyze the transmission mechanization of interest rate in China by facilitating numerous time series data and Factor Augmenting Vector Autoregression Model, analyzing the relationships between interest rate and macroeconomic variables.
然后分析中国利率传导机制，并采用大量的经济时间序列数据和要素增强型向量自回归模型对利率与宏观经济变量的相关性进行实证分析。 - The first part of paper simply introduce wind farm wind speed forecasting mode, and introduce time series, neural network, support vector machine, least squares support vector machines into wind speed forecasting model.
论文前部分主要介绍了风电场风速预测模型，将时间序列法、神经网络法、支持向量机和最小二乘支持向量机理论引入风速预测模型。 - In this paper, the main experimental Shanghai Composite Index for the week of the closing price, and time series forecasting models and support vector machine algorithm to predict.
本文的实验主要针对上海综合指数的周收盘价，采用时间序列预测模型和支持向量机算法进行预测。 - The searching capabilities of overall situation robust of ant colony algorithm make some contribution to improve prediction accuracy rate of time series prediction model based on support vector machines.
蚁群算法强劲的全局搜索能力，对提高基于支持向量机的时间序列预测模型的预测准确率有一定的贡献。 - The results indicate that least squared support vector machine prediction model of multivariate time series outperforms least squared support vector machine prediction model of univariate time series. The results have very important theory and practice sense for nonlinear modeling and forecasting of futures prices.
结果表明多变量时间序列最小二乘支持向量机预测模型要优于单变量时间序列最小二乘支持向量机预测模型，这一结论对期货价格的非线性建模和预测具有重要的理论意义和现实意义。 - And then introduced three single forecasting methods used in railway passenger volume prediction: multiple regression analysis prediction, time series prediction, support vector machine regression analysis.
接着介绍了应用于铁路客运量预测的三种单一预测方法：多元线性回归分析预测法、时间序列分析预测法以及支持向量机回归分析预测法。 - Based on achievement of comprehensive time series forecasting and neural network prediction, the paper proposed price forecasting model of mixed time series based on support vector machines.
通过综合时序预测和神经网络预测的研究成果，提出基于改进支持向量机的时序混合电价预测模型。