搜索资源列表
NONOBS
- 使用结构时间序列对比利时每年的GDP数据进行建模- use structural time series models build a model for annual Belgium GDP data,
20110619-3
- 使用动态数据建模(DDS)法与Box—Jenkins建模法相结合的方法建立时间序列模型，使两种 方法的优。最互相结合起来，简化了现有的建模过程。在使用MATLAB进行仿真后，快速、方便地得到了相 应的模型。该方法能较快地完成建模，较适用于对模型精度要求不太高的地方。-Using dynamic data modeling (DDS) method and the Combination of Box-Jenkins modeling method to establish time-se
shijianxulie
- 时间序列算法，建立AR模型，进行功率谱分析，Green函数等。-Time Series algorithm, the establishment of AR model, power spectrum analysis, Green function and so on.
c
- This a time series analysis matlab under the ARMA model and prediction procedures. ARMA algorithm by using a series of data to predict and analyze the prediction rule -This is a time series analysis matlab under the ARMA model and prediction proce
A-hybrid-least-squares
- A hybrid least squares support vector machines and GMDH approach for river fl ow forecasting-This paper proposes a novel hybrid forecasting model, which combines the group method of data handling (GMDH) and the least squares supp
Adaptive-Embedding-Dimension
- 嵌入维数自适应最小二乘支持向量机 状态时间序列预测方法 Condition Time Series Prediction Using Least Squares Support Vector Machine with Adaptive Embedding Dimension 针对航空发动机状态时间序列预测中嵌入维数难于有效选取的问题, 提出一种基于嵌入维数自适应 最小二乘支持向量机( L SSVM ) 的预测方法。该方法将嵌入维数作为影响状态时间序列预测精度的重要参
Xinying_Ph.D.thesis
- SUPPORT VECTOR MACHINE IN CHAOTIC HYDROLOGICAL TIME SERIES FORECASTING 支持向量机混沌时间序列预测-This research attempts to demonstrate the promising applications of a relatively new machine learning tool, support vector machine, on chaotic hyd
Sample-Entropy-VB
- 样本熵是一种有别于近似熵的不计数自身匹配的统计量，是对于近似熵算法的改进。样本熵与近似熵的物理意义一样，表示非线性动力学系统产生新模式概率的大小，主要用来定量刻画系统的规则度及复杂度。样本熵值越低，序列自我相似性越高，产生新模式的概率越低，时间序列越简单；反之，样本熵值越大，序列自我相似性越低，产生新模式的概率越高，时间序列越复杂。样本熵计算用程序VB6.0语言实现。-Sample entropy is different from the research and development o
ARIMA
- 时间序列预测ARIMA模型，这是一种基于风速数据的预测程序。-ARIMA time series forecasting model, which is a program based on the forecast wind speed data.
dsf2
- 基于RBF_HMM模型的时间序列在线预测.Based on the RBF_HMM model of time series forecasting.-Based on the RBF_HMM model of time series forecasting.
Application-of-optimized-Elman--
- 对量子粒子群优化(QPSO) 算法进行研究，提出了自适应量子粒子群优化(Adaptive QPSO) 算法，用于优化Elman 神经 网络的参数，改进了Elman 神经网络的泛化能力。利用网络流量时间序列数据进行预测，实验结果表明，采用AQPSO 算法优 化获得的Elman 神经网络模型不但具有较强的泛化能力，而且具有良好的稳定性，在网络流量时间序列数据的预测中具有 一定的实用价值-Quantum-behaved particle swarm optimization (QPSO)
svm_time
- 做时间序列预测的svm程序,matlab编的，多种时间序列预测模型-Time series prediction svm program, matlab code, and a variety of time-series forecasting model
Improved-Elman-share-price-forecast
- 以深 市 A股中的个股 中集集团(股票代号 ： 000039)fleJ 180天的实际收盘价的时间序列作为预测对象，提出基于改进的 Elman神经网络的个股价格预测模型，实验 结果取得较高的预测精度、较为稳定的预测效果和较快的收敛速度-CIMC Shenzhen A-share stocks (ticker symbol: 000 039) fleJ 180 days of the actual closing price time series as a predictor of
gm3
- 指数形式的时间序列的灰度预测模型 Gray prediction model of the exponential form of time series-Gray prediction model of the exponential form of time series
AR
- 时间序列分析中的AR模型的matlab简单实现,一个小例子，适合刚入门者使用-Simple implementation of the AR model in time series analysis, a small example, suitable for just beginners
containerforecast_stepwisefit
- 使用stepwise方法选择因变量的基于AR模型的时间序列预测程序-This alogrithm can select the predictors using step-wise policy and forecast the time series based on AR model.
armadj
- 用于时间序列ARMA模型定阶程序,效果还可以，供大家参考！-a program for Time Series ARMA model order determination
Timeprediction-AR-MATLAB
- 时间序列AR模型预测的matlab源文件，可直接运行，有仿真结果。-Time series prediction of the AR model matlab source file, can be directly operation, the simulation results.
AR
- matlab写的用于时间序列预测的AR模型的程序，对于线性的时间序列效果还是可以的。-Matlab written procedures for time series forecasting AR model, the linear effect of time-series.
t1
- 运用matlab编程计算时间序列中的ARMA（p,q）模型-Use of matlab programming to calculate the time series ARMA (p, q) model