Through incremental integration and independent research and development, build a method library of big data quality control, automatic modeling and analysis, data mining and interactive visualization, form a tool library with high reliability, high scalability, high efficiency and high fault tolerance, realize the integration and sharing of collaborative analysis methods of multi-source heterogeneous, multi-granularity, multi-phase, long-time series big data in three pole environment, as well as high Efficient and online big data analysis and processing.
Auto-regressive is a model of stationary time series.
Installation mode: Install MATLAB;
Operation mode: Running on MATLAB;
Input variables: Time series data;
Output variables: Time series predictive value;
Dependent library files: Packed into the Dependent function folder
QR code:
1656 2019-10-14 View Details
Auto-regressive moving average is a model of stationary time series.
Installation mode: Install MATLAB;
Operation mode: Running on MATLAB;
Input variables: Time series data;
Output variables: Time series predictive value;
Dependent library files: Packed into the Dependent function folder
QR code:
2104 2019-10-16 View Details
Moving average is a model of stationary time series.
Installation mode: Install MATLAB;
Operation mode: Running on MATLAB;
Input variables: Time series data;
Output variables: Time series predictive value;
Dependent library files: Packed into the Dependent function folder
QR code:
1802 2019-10-15 View Details
Auto-regressive intergrated moving average is a model of nonstationary time series.
Installation mode: Install MATLAB;
Operation mode: Running on MATLAB;
Input variables: Time series data;
Output variables: Time series predictive value;
Dependent library files: Packed into the Dependent function folder
QR code:
3623 2019-10-18 View Details
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