搜索资源列表
predict_fun
- 基于均值生成函数时间序列预测算法程序 1. predict_fun.m为主程序 2. timeseries.m和 seriesexpan.m为调用的子程序 -function based on the mean generation time series prediction algorithm for a procedure. Predict_fun.m mainly procedures 2. Timeseries.m seriesexpan.m and called for
arimapred
- ＡＲＩＭＡ matlab实现 ， 对时间序列进行预测分析
ARMA
- 这是一个在matlab下时间序列分析ARMA模型的建立和预测程序。
lbg
- 随着新的数学工具小波分析的实用化为基于NN负荷预测模型性能的改善提供了理论依据对于电力系统负荷非线性时间序列的辨识在预测方法研究中应给予重视在本文所用的基于小波原理和NN融合的预测原理是具有强的非线性-With the new mathematical tools of wavelet analysis into practical load forecasting model based on the performance of NN provides a theoretical basis
lu
- 在用混沌理论和神经网络进行短期负荷预测时，神经网络的输入的选择至关重要，该程序用matlabl实现了基于混沌时间序列的嵌入维数的选择-In chaos theory and neural networks with short-term load forecasting, neural network is essential to choose the input, the program implemented with matlabl chaotic time series based o
nu
- 一个多输入多输出小波网络的源程序，用matlab编写，能够实现对时间序列数据的训练预测-A multi-input multi-output wavelet network' s source code, written with matlab, can be achieved on the training time series data forecasting
Nonlinear-analysis-to-stock-market
- (股市)非线性分析及预测工具箱，整合了原非线性时间序列分析工具箱程序，包含多个复杂度分析(如Higuchi法、计盒法)，相空间重构(Cao法、GP算法、互信息法)，最大李雅普诺夫指数判断(Wolf法、小数据法)和预测程序(lyp指数法、一次多步预测等)，程序执行效率高，实测可用。-Nonlinear analysis and prediction toolbox (stock market), the integration of the original nonlinear time seri
matlab-
- 神经网络对时间序列的观测时序进行预测，预测精度高，可以在工程上应用-Neural network to predict the timing of time-series observations, the prediction accuracy is high, can be applied in engineering
BP-forecast.m
- BP神经网络实现人口预测，时间序列预测，值得一看，学习-BP neural network population forecasts, time series forecasting, see, learn
ARIMAyubao
- 建立自回归滑动平均时间序列模型ARIMA,用来预测未来数据值-time series model-ARIMA to predict the future value
2013061684653145
- Matlab代码，实现时间序列的MA模型的属于预测-Matlab code, time series models are predicting MA
ARMA
- ARMA时间序列模型预测，内附详解，可以作为参数识别的参考程序。-ARMA time series model predicts that included Detailed can be used as a reference parameter identification procedure.
MG_RK4
- Mackey-Glass时间序列预测建模问题，对数据采用4阶龙格库塔方法离散化。-Mackey-Glass time series prediction modeling of data using four discrete order Runge-Kutta method.
MLP_MG
- Mackey-Glass时间序列预测建模问题，建立了四输入一输出、具有3层结构的MLP人工神经网络，实现了函数逼近的功能。-Mackey-Glass time series prediction modeling, the establishment of a four-input one output, with a 3-layer MLP artificial neural network architecture to achieve a function approximation fu
GM1_1_C.m
- 改进c灰色预测方法的matlab程序，一维时间序列数据可直接使用-Improved gray prediction method c matlab program, one-dimensional time-series data can be used directly
ARIMA1
- 利用ARIMA方法对时间序列进行短期预测，适合初学者。-To predict the time series by using the ARIMA method, suitable for beginners.
SVM
- 基于支持向量机的对于上证指数的时间序列的预测，附有相关的论文期刊-Support vector machine for forecasting time series of Shanghai Composite Index and related papers
BP-network
- 基于小波神经网络的时间序列预测—短时交通流量预测-Short-term traffic flow prediction based on wavelet neural network
huiseBP
- 实现时间序列的灰色神经网络预测，可以参考-gery bp network
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。