搜索资源列表
自适应算法
- matlab程序,用于计算时间序列中的自适应问题可以进行预测-Matlab procedures used in the calculation of time-series of adaptive problems can be predicted
AOLMM
- 基于局域法多步预报模型的混沌时间序列预报模型,对多个典型混沌序列的仿真测试表明,本算法具有良好的多步预测精度和较好的抗噪声能力-based multi-step prediction model of chaotic time series prediction model, a number of typical chaotic sequence of simulation tests show that the algorithm has a good multi-step forecast
Volterraprediction
- 小数据量法求混沌吸引子最大Lyapunov指数的Matlab程序,参考文献:张家树.混沌时间序列的Volterra自适应预测.物理学报.2000.03-small data method for chaotic attractor largest Lyapunov exponent of Matlab procedures References : Zhang Shu. The chaotic time series Volterra adaptive prediction. Physics
Volterraprediction1
- 混沌时间序列的Volterra一步预测的Matlab程序-chaotic time series forecast Volterra step procedure Matlab
Volterra_hwg
- 在MATLAB上实现混沌时间序列的Volterra预测算法-in MATLAB achieve chaotic time series prediction algorithm Volterra
biyelunwenkaitibaogao
- 基于时间序列数据预测方法的股市收盘价预测的毕业论文开题报告(理工类)-based on the time series data to predict the stock market means closing price forecasts dissertation problem that report (Polytechnic)
Volterra_MultiStepPred_luzhenbo
- 基于Volterra滤波器混沌时间序列多步预测 作者:陆振波,海军工程大学 欢迎同行来信交流与合作,更多文章与程序下载请访问我的个人主页 电子邮件:luzhenbo@sina.com 个人主页:luzhenbo.88uu.com.cn 参考文献: 1、张家树.混沌时间序列的Volterra自适应预测.物理学报.2000.03 2、Scott C.Douglas, Teresa H.-Y. Meng, Normalized Data Nonlineariti
timeseries
- 用小波神经网络来对时间序列进行预测,其中有四个m文件-wavelet neural network to forecast the time series, which document 4 m
LSTM_main
- LSTM(Long Short-Term Memory)是长短期记忆网络,是一种时间递归神经网络,适合于处理和预测时间序列中间隔和延迟相对较长的重要事件。(LSTM (Long Short-Term Memory) is a long and short term memory network. It is a kind of time recurrent neural network, which is suitable for dealing with and predicting impo
c-c算法计算时间tau
- 在混沌时间序列方法进行风电功率预测用C-C算法tau时间(C-C algorithm tau time for wind power prediction using chaotic time series method)
code
- 数据处理预测;时间序列;前期数据处理;后期GRU预测(Data processing prediction)
LSTM2
- LSTM可用的matlab程序,可用到时间序列预测(Matlab code for predicting via LSTM algorithm)
ARMA-master
- 程序附带说明,时间序列预测模型ARMA模型,非平稳时间序列预测(Program with instructions, time series prediction model ARMA)
LargestLyapunov_Rosenstein
- 混沌时间序列预测中,重构相空间采用小数据量法求取最大李雅普莫诺夫指数。(In the prediction of chaotic time series, the maximum lyapunov index is obtained by the method of small data quantity in the reconstructed phase space.)
23_time_series_prediction
- 用 Python 机器学习,时间序列模型预测, 循环神经网络(Python Machine Learning, Time Series Model Prediction, recurrent Neural Network)
ARMA
- 利用ARMA时间序列模型 预测短期内风速(Forecasting wind speed with ARMA)
电力负荷组合预测
- 基于svM以及时间序列法的短期电力负荷预测,MATLAB源代码 谢谢
ruan zhu
- 一个用DBN做时间序列预测的实例,内包括了数据(An example of using DBN to predict time series includes data)
Python深度学习实战_原书代码
- 深度学习正在为广泛的行业带来革命性的变化。对于许多应用来说,深度学习通过做出更快和更准确的预测,证明其已经超越人类的预测。本书提供了自上而下和自下而上的方法来展示深度学习对不同领域现实问题的解决方案。这些应用程序包括计算机视觉、自然语言处理、时间序列预测和机器人。(Deep learning is bringing revolutionary changes to a wide range of industries. For many applications, deep learning p
GRU预测模型
- 使用python编程,对时间序列进行预测建模。参数较少,预测比较准确,运行时间快。