Multiple regression of the related factors on the attack rate of influenza outbreak in Hangzhou city;

A method of optimizing a candidate zone to be fractured with multiple regression and neural network is put forward in the paper because there are some problems in Wuliyasi Sag, such as strong reservoir heterogeneity, poor interlayer shielding, big difference between fractured wells and it is hard to select good candidate wells.

Then we put forward the computation formula for base distortion and energy consumption of multiple regression with fortified intensity, base thickness and liquid level.

For the problem that the dependent variable has many independent variables and their sampling periods are also different, a predicting method is proposed by using synthetically the data analysis methods of support vector regression (SVR), multivariate regression and principal component analysis, etc.

The inherent laws behind the numerical data were discovered after the data were processed by the multivariate regression model and computer simulation.

The multivariate regression has two defects.

We avoid the interfere of different elements with the multiple linear regression on spectra and BGO Gamma-ray detector.

The multiple linear regression method is applied to deal with data solving the interferential problem of multiple elements.

The multiple linear regression is used on spectra in order to avoid the interfere of different elements.

By the method of multi-regression, this article analyses the determinant factors in Chinese business insurance demand on the basis of the data of 1985-1999 and the present development of business insurance markets in China.

The process of establishing the multi-regression model and the four possible forms of variables reaching significant level are studied.

The model of multi-regression cannot correctly distinguish the direct and indirect effects from different components in the process of building because the measuring units have differences.