搜索资源列表
ARIMA_model
- 基于MATLAB的ARIMA模型的源代码。ARIMA模型是自回归滑动平均求和模型，是时间序列分析模型，可以用于时间序列的预测。该代码实现了ARIMA模型的建模和谱分析过程-The ARIMA model based on MATLAB source code. ARIMA model is the sum of autoregressive moving average model is time series analysis models, can be used for time seri
arima
- arima model to forecaste time series
cpp
- This paper presents an on-line Statistical Process Control (SPC) technique, based on a Generalized Likelihood Ratio Test (GLRT), for detecting and estimating mean shifts in autocorrelated processes that follow a normally distributed Autoregressive In
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.
ARIMA
- ARM 用于数学建模的时间序列 预测问题 -ARM used for mathematical modeling time series prediction problem
ARIMA-model-algorithm
- 。统计预测方法建立在严密 的数学理论基础之上，具有结构简单、预测速度快、方便操作等特点，相对于其 他时序分析预测方法(如:回归分析、神经网络等)更适合实际应用 -. Statistical prediction method is based on a rigorous mathematical basis of the theory with a simple structure, the forecast fast, convenient operation, relative
adaboost-emd-wavelet-ARIMA
- emd/wavelet信号处理的matlab程序 ARIMA时间序列matlab预测程序 单纯形法matlab程序 图论算法及其matlab代码 adaboost原理及代码-emd/wavelet signal processing matlab program ARIMA time series matlab prediction program simplex method matlab program graph theory algorithm matlab code a
Series-Forcast
- 用于时间序列的预测，包含序列特征描述、平稳性检验、序列周期判断、季节因子提取、指数平滑预测、及ARIMA预测-Sequence features for time series prediction, including the descr iption of the stationary test, to determine the sequence cycle, seasonal factor extraction, exponential smoothing, and ARIMA fore
ARIMA
- arima time series matlab 时间序列预测程序-arima timeseries matlab
arima
- 数据挖掘 人工智能 时间序列预测模型 matlab学习-Data Mining Artificial Intelligence Time series forecasting model matlab learning
arima
- 时间序列中，ARIMA（1,1,1）模型实例，通过计算得到这一过程的十步预测-Time series, (1,1,1) model instance ARIMA, obtained by calculating this process ten-step prediction
arima
- arima时间序列模型，对一个序列进行也测-arima time series models, also measured on a sequence
ARIMA
- 使用时间序列进行短时交通预测的小程序-Using time series of short-term traffic forecasts applet
Time_Series_Analysis
- ARIMA算法的Python实现，预测时间序列数据。 附两个数据： AirPassengers UK Traffic flow(The Python implementation of the ARIMA algorithm predicts the time series data. Two data are attached. AirPassengers UK Traffic flow)
ARIMA
- arima算法实现思路，主要用来进行时间序列预测(The realization of ARIMA algorithm is mainly used for time series prediction)
Dissertation-ARIMA_SVR-prediction-master
- 基于时间序列分析ARIMA和SVR组合模型的预测(Prediction of ARIMA and SVR combined models based on time series analysis)
time-series-forecasting-keras-master
- 基于ARIMA模型和LSTM模型，提出一种高性能得时间序列预测算法(Based on ARIMA model and LSTM model, a high performance time series prediction algorithm is proposed.)
ARIMA预测
- ARIMA整合移动平均自回归模型，时间序列预测分析方法之一，可用于股价预测。(ARIMA integrates moving average autoregressive model and time series forecasting analysis method, which can be used for stock price forecasting.)
arima
- arima - （平稳性检验）根据时间序列的散点图、自相关系数和偏自相关系数、单位根检验(ADF)，来判断数据的平稳性； - （平稳化处理）对非平稳的时间序列数据进行差分处理，得到差分阶数d； - （白噪声检测）为了验证序列中有用的信息是否已被提取完毕，如果为白噪声序列，(arima arima -(Stableness test) According to the time series of scatter plots, autocorrelation coefficients and
ARIMA
- ARIMA 模型是在平稳的时间序列基础上建立起来的，因此时间序列的平稳性是建模的重要前提。检验时间序列模型平稳的方法一般采用 ADF 单位根检验模型去检验。当然如果时间序列不稳定，也可以通过一些操作去使得时间序列稳定（比如取对数，差分），然后进行 ARIMA 模型预测，得到稳定的时间序列的预测结果，然后对预测结果进行之前使序列稳定的操作的逆操作（取指数，差分的逆操作），就可以得到原始数据的预测结果。(time series prediction ARIMA)