SPA- System process analysis

New Square Method

◆ "New square method" is an improved method of "least square method", and "least square method" is a special case of "new double multiplication". It can replace all the previous regression analysis algorithms. It not only calculates the constants and coefficients of the model, but also calculates the power value in the model variables, making the regression analysis simpler and the results more accurate.

◆ "New square method" in regression processing of two-dimensional data, a variable can derive multiple elements with different powers of the same variable. When processing multi-dimensional data, considering the interaction of different variables, multiple elements can be derived to make the regression analysis results more accurate.

Dynamic local analysis

◆ "Dynamic local analysis" is an algorithm for big data analysis.

◆ Big data has many dimensions, a wide range and a large amount of data, and it is difficult to find the mathematical relationship between them with the "New square method". For the first problem, we developed the "Dynamic local analysis" method.

◆ "Dynamic local analysis" is to screen the original historical data and eliminate unreasonable samples to obtain N groups of samples. During sample analysis, find the k (k can be set as 10) sample closest to the sample in N groups of samples, use k sample to model, and substitute the sample data into the model for calculation, and the calculation results meet the accuracy requirements.