搜索资源列表
laiqen
- 使用matlab实现智能预测控制算法,LZ复杂度反映的是一个时间序列中,基于欧几里得距离的聚类分析。- Use matlab intelligent predictive control algorithm, LZ complexity is reflected in a time sequence, Clustering analysis based on Euclidean distance.
nou-V3.6
- 时间序列数据分析中的梅林变换工具,实现典型相关分析,可以广泛的应用于数据预测及数据分析。- Time series data analysis Mellin transform tool, Achieve canonical correlation analysis, Can be widely used in data analysis and forecast data.
AR_predict
- 基于时间序列的自回归AR模型预测,有具体的注释-The autoregressive AR model based on time series prediction, a specific comments
hu514
- 阐述了负荷预测的应用研究,LZ复杂度反映的是一个时间序列中,研究生时的现代信号处理的作业。- It describes the application of load forecasting, LZ complexity is reflected in a time sequence, Modern signal processing jobs when the graduate.
withDAE
- 数据预处理、时间序列法确定参数、建立模型、预测-Data preprocessing, time series method to determine the parameters, model, forecast
GM(1-1)-model-
- GM(1,1)残差预测模型,用于预测指数或对数规律的时间序列-GM (1,1) residual prediction model for predicting the time series of exponential or logarithmic laws
BP_Hidden
- 双隐层BP神经网络实现,功能为时间序列的预测。-Double hidden layer BP neural network, the function of time series prediction.
fiupie-V8.3
- LZ复杂度反映的是一个时间序列中,使用matlab实现智能预测控制算法,isodata 迭代自组织的数据分析。- LZ complexity is reflected in a time sequence, Use matlab intelligent predictive control algorithm, Isodata iterative self-organizing data analysis.
chap-6
- MATLAB处理时间序列数据分析使用指数平滑预测模型编程代码-ES code
0644
- 使用matlab实现智能预测控制算法,LCMV优化设计阵列处理信号,时间序列数据分析中的梅林变换工具。- Use matlab intelligent predictive control algorithm, LCMV optimization design array signal processing, Time series data analysis Mellin transform tool.
7680
- 滤波求和方式实现宽带波束形成,可以广泛的应用于数据预测及数据分析,LZ复杂度反映的是一个时间序列中。- Filtering summation way broadband beamforming, Can be widely used in data analysis and forecast data, LZ complexity is reflected in a time sequence.
time-series-to-build-wear-model
- 使用C++语言编程建立时间序列模型,进行磨损预测-Use C++ language programming to build time series model for wear prediction
111
- 使用ARMA模型建立数学模型做时间序列的预测-Using the ARMA model to establish a mathematical model for prediction
4763
- 时间序列数据分析中的梅林变换工具,非归零型差分相位调制信号建模与仿真分析 ,未来线路预测,分析误差。- Time series data analysis Mellin transform tool, NRZ type differential phase modulation signal modeling and simulation analysis, Future line prediction, error analysis.
mntersection
- 在MATLAB上实现混沌时间序列的Volterra预测算法 不错的-On MATLAB implementation on the prediction of chaotic time series algorithm is good
aopend
- 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-Based on the chaotic time series multi-step prediction filter author: Liu Zhenbo, naval engineering university
jttim
- 时间序列数据分析中的梅林变换工具,music高阶谱分析算法,可以广泛的应用于数据预测及数据分析。- Time series data analysis Mellin transform tool, music higher order spectral analysis algorithm, Can be widely used in data analysis and forecast data.
chaosToolBoxVersion2.9
- 1、该工具箱包括了混沌时间序列分析与预测的常用方法,有: (1)产生混沌时间序列(chaotic time series) Logistic映射 - \ChaosAttractors\Main_Logistic.m Henon映射 - \ChaosAttractors\Main_Henon.m Lorenz吸引子 - \ChaosAttractors\Main_Lorenz.m Duffing吸引子 - \ChaosAttractors\Main_Duffing.m Duffin
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 to study time series. It consists of auto
rbf
- RBF神经网络,可实现对风速预测等时间序列的预测(RBF neural network which can be used to predict time list)