搜索资源列表
rnn
- rnn maltab时间序列预测实现,深度学习时间序列预测实现-realization of RNN
time-gp-programer
- 时间序列预测的GP程序,我认为比较实用。-Time series forecasting GP program, I think it more practical.
chaotic
- 混沌时间序列是一种确定系统中出现的无规则的运动,内含混沌时间序列预测程序。-It is a chaotic time series to determine the random motion present in the system, containing chaotic time series prediction program.
Mackey-Glass-Time-Series-Forecasting
- 用模糊预测混沌时间序列预测方法的matlab程序,很好用-Mackey-Glass Time Series Forecasting using Method 1 Single Stage Fuzzy Forecaster
wavelet-neural-network
- 小波神经网络的时间序列预测——短时交通流量预测-Time series forecasting based on wavelet neural network- short- term traffic flow forecasting
holt_winters
- holt-winters 三次指数平滑算法,时间序列预测算法,带测试数据及Demo-Triple Order Exponential Smoothing, Holt-Winters algorithm, time series prediction algorithm with test data and Demo
svmTime-series-prediction
- matlab环境下的支持向量机的时间序列预测-Time Series Prediction of Support Vector Machine in Matlab Environment
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
Prediction_RBF
- 混沌时间序列预测(chaotic time series prediction) RBF神经网络一步预测 - \Prediction_RBF\Main_RBF.m RBF神经网络多步预测 - \Prediction_RBF\Main_RBF_MultiStepPred.m Volterra级数一步预测 - \Prediction_Volterra\Main_Volterra.m Volterra级数多步预测 - \Prediction_Volterra\Main_Volterra
Time-Series-Analysis-and-Forecast
- 时间序列预测的GUI仿真,可以直接输入时间序列数据进行预测-GUI:Time Series Analysis and Forecast
wavenn
- 小波神经网络的时间序列预测-短时交通流量预测-Time series prediction of short term traffic flow forecasting based on Wavelet Neural Network
Elman
- ELMAN神经网络时间序列预测,带有数据值-ELMAN neural network time series prediction With the data values
OMYIF71
- 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
chapter32
- 小波神经网络的时间序列预测——短时交通流量预测-Wavelet neural network time series prediction of short-term traffic flow forecasting
512806
- 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
test
- 用于研究时间序列的方法有AR(自回归)、MA(滑动平均)、ARMA(自回归滑动平均)这三种模型。而对于一个平稳时间序列预测问题,首先要考虑的是寻求与它拟合最好的预测模型。而模型的识别与阶数的确定则是选择模型的关键。 1.用 迭代生成1000个点(前2个点自定义)。 2.在这1000个点中取800点进行时间序列分析建立合适的模型。 3.利用剩余的200个点进行模型预测,并看其是否匹配,最后校正。 -Methods for studying time series are AR (a
ARMA
- ARMA 模型(Auto-Regressive and Moving Average Model)是研究时间序列的重要方法,由自回归模型(简称AR模型)与滑动平均模型(简称MA模型)为基础“混合”构成。在市场研究中常用于长期追踪资料的研究,如:Panel研究中,用于消费行为模式变迁研究;在零售研究中,用于具有季节变动特征的销售量、市场规模的预测等。(ARMA model is an important method for studying time series. It is composed
www.dssz.com_dssz
- 混沌时间序列预测中的李雅普诺夫指数算法,判断时间序列的混沌特性(The Lyapunov exponent algorithm in chaotic time series prediction is used to determine the chaotic characteristics of time series)
新建文件夹 (6)
- 计算数据得未来数据值,可对数据进行预测 具有和好的通用性(Calculate the data for future data values, and predict the data with good versatility)
time series model
- 时间序列分析是根据系统观测得到的时间序列数据,通过曲线拟合和参数估计来建立数学模型的理论和方法。它一般采用曲线拟合和参数估计方法(如非线性最小二乘法)进行。时间序列分析常用在国民经济宏观控制、区域综合发展规划、企业经营管理、市场潜量预测、气象预报、水文预报、地震前兆预报、农作物病虫灾害预报、环境污染控制、生态平衡、天文学和海洋学等方面。(Time series analysis is the theory and method of establishing mathematical model