搜索资源列表
ARIMAtest
- 对于时间序列模型建立ARMA预测模型,可对未来值进行预报。(For the time series model, the ARMA prediction model is established, and the future value can be forecasted.)
数学建模思想方法大全及方法适用范围
- 时间序列预测法是一种定量分析方法,它是在时间序列变量分析的基础上, 运用一定的数学方法建立预测模型,使时间趋势向外延伸,从而预测未来市场的 发展变化趋势,确定变量预测值。(Time series forecasting method is a quantitative analysis method. It is based on the analysis of time series variables,A mathematical model is used to establish a
sitay_calculating
- C-C方法计算时间延迟和嵌入维数计算Lyapunov指数计算关联维数混沌时间序列预测,(C - C time delay and embedding dimension method to calculate the Lyapunov index calculating correlation dimension chaotic time series prediction,)
hurst指数
- hurst指数主要用于预测时间序列的未来变化趋势(Mainly used to predict the future trend of time series trends)
817671
- 用matlab实现利用统计混沌方法解决非线性系统时间序列预测的问题(Matlab to make use of statistical chaos method to solve the problem of nonlinear system time series prediction)
程序2
- 灰色理论认为系统的行为现象尽管是朦胧的,数据是复杂的,但它毕竟是有序的,是有整体功能的。灰数的生成,就是从杂乱中寻找出规律。同时,灰色理论建立的是生成数据模型,不是原始数据模型,因此,灰色预测是一种对含有不确定因素的系统进行预测的方法。(The grey theory holds that although the behavior of the system is obscure and the data is complex, it is orderly and integral. The
LSTM_learn-master
- 采用LSTM算法用python语言实现的信号时间序列预测,可预测信号的占用度(The LSTM algorithm is used to predict the signal time series in python language)
ARIMA
- 可以很好的预测数据,程序代码简单可靠好用(Good prediction of data, the program code is simple and reliable easy to use.)
transnction-smart-form
- 时间序列预测法是一种定量分析方法,它是在时间序列变量分析的基础上,运用一定的数学方法建立预测模型,使时间趋势向外延伸,从而()
arimanet
- ARIMA模型全称为自回归积分滑动平均模型(Autoregressive Integrated Moving Average Model,简记ARIMA),是由博克思(Box)和詹金斯(Jenkins)于70年代初提出一著名时间序列预测方法[1] ,所以又称为box-jenkins模型、博克思-詹金斯法。其中ARIMA(p,d,q)称为差分自回归移动平均模型,AR是自回归, p为自回归项; MA为移动平均,q为移动平均项数,d为时间序列成为平稳时所做的差分次数。所谓ARIMA模型,是指将非平稳
ARMA
- 采用MATLAB实现arma时间序列的建模与预报(Modeling and forecasting of ARMA implementation time series)
lstm-oreilly-master
- 时间序列预测,股票走势预测,自然语言处理等等(Time Series Prediction)
LSSVM
- lssvm用于时间序列预测的matlab程序(LSSVM for time series prediction)
elmen网络代码
- ELMAN神经网络模型预测精度高于BP神经网络,可以用于非线性时间序列的预测。(The prediction accuracy of ELMAN neural network model is higher than that of BP neural network, and it can be used to predict nonlinear time series.)
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)
lstm
- 使用lstm神经网络预测时间序列,同时对参数选择进行优化(Time series prediction using LSTM neural network, the selection of the parameters are optimized)
yesllmg6
- 时间序列预测法是一种定量分析方法,它是在时间序列变量分析的基础上,运用一定的数学方法建立预测模型,使时间趋势向外延伸,从而()
loess-master
- 局部加权平均算法,用于时间序列预测,大家看着给点好处就好(Local weighted average algorithm for time series prediction.)
lssvm_prediction
- LSSVM时间序列预测,基于matlab lssvm工具箱!推荐!!!!!(LSSVM time series prediction is based on MATLAB LSSVM toolbox. Recommend!!!!!)
sjyc
- 时间预测的应用需要garchset.m,在2012版本以上的可能无法实现(The application of time prediction needs garchset.m)