6 results about "Multiple regression equation" patented technology

The invention belongs to the technical field of personnel efficiency prediction and selection, and particularly relates to a behavior efficiency prediction method based on psychological characteristics. According to the method, corresponding psychological indexes and behavior efficiency evaluation indexes are established for nuclear power master control room operators, correlation analysis is adopted to explore the relationship between psychological quality and behavior efficiency, and a behavior efficiency prediction model based on psychological quality is established based on a multiple regression equation. The technical problem of how to improve the working efficiency of a nuclear power plant and further prevent human errors by improving the adaptability of psychological conditions and post requirements of nuclear industry personnel is solved.

An induction energy transmission system includes a set-down plate, a supply unit including a supply induction element arranged below the set-down plate and designed to inductively provide energy, a set-down unit including a receiving unit with a receiving induction element designed to receive the inductively provided energy, and a control unit designed to control the supply unit by using a parameter set so as to control the supply unit and to receive a parameter of the parameter set from the set-down unit. The control unit receives in addition an information parameter set from the set-down unit to determine a coefficient of a multivariable regression equation and based on the coefficient to determine a correction factor for a parameter of the parameter set or determine a new parameter set.

This technology improves the accuracy of predicting material thinning by considering multiple different flow conditions. [Solution] The thinning prediction system comprises a fluid simulator 3 that calculates fluid analysis values ​​by fluid simulation using the amount of thinning in the test piece 10 as a result of a water flow corrosion test and the shape of the test piece 10 for a test piece 10 used in a water flow corrosion test; a multiple regression equation generation unit 4 that generates a thinning prediction equation with the amount of thinning as the objective variable and the fluid analysis values ​​as the explanatory variables; and a thinning amount calculation unit 5 that calculates the amount of thinning in the target pipe based on the shape data of the target pipe and the thinning prediction equation, wherein the thinning prediction equation is a combination of multiple provisional prediction equations generated under different flow conditions in the test piece 10.

The invention discloses a sea area plankton density prediction method based on environmental factors and acoustics, and belongs to the technical field of marine organism prediction.The sea area plankton density prediction method comprises the steps that multi-source data are obtained from a target sea area, and the multi-source data comprise acoustic echo data and environmental factor data; extracting a noise level from the acoustic echo data; judging whether the noise level exceeds a preset threshold value or not, and if yes, performing denoising processing on the acoustic echo data to obtain a pure acoustic signal feature set; normalizing the features in the pure sound wave signal feature set and the environmental factor data; and obtaining an estimation result of the plankton distribution density through a multiple regression equation according to the normalized pure acoustic signal characteristics and the environmental factor data. The sea area plankton density prediction method based on environmental factors and acoustics solves the problem of inaccurate prediction caused by complex marine environment in the aspect of plankton density prediction at present.

The application provides a CTMU-based adaptive variable current source ultrasonic flow measurement method, and belongs to the technical field of downhole pipeline flow measurement. The method comprises the following steps: adopting a least square method to establish a flow rate influencing factor matrix, a measured flow rate matrix, a residual variable matrix and an unmeasured flow rate matrix; based on the flow rate influencing factor matrix, the measured flow rate matrix, the residual variable matrix and the unmeasured flow rate matrix, a multiple regression equation is established; based on the multiple regression equation, the unmeasured flow rate of fluid in a downhole pipeline is predicted; or, according to the measured flow rate and the flow rate influencing factor, a sum of squared deviations of the measured flow rate is calculated; and based on the sum of squared deviations of the measured flow rate, the unmeasured flow rate is predicted. The application can improve the accuracy of ultrasonic flow measurement and has strong ease of use and practicality.

This invention discloses a method for constructing evaluation indicators for power batteries of pure electric vehicles based on big data analysis, including the following steps: A1. Marking the vehicles; A2. During the operation and use of the P1th vehicle; A3. The P2th...P... n Repeat steps A2 and A5 for each new car, and remove the first DB. ND The parameters are based on the data before the 1% mark and the data after the 99th mark following a normal distribution. A6. Use the labeled samples as the target values. A7. Use neural network models MM1...MM. n The calculated values ​​at each sampling point are used as the dependent variable. A8. Regression analysis is used. A9. One or more regression equations with the lowest overall error rate are extracted from the multiple regression equations and used as a continuous parameter prediction model. Compared with traditional neural network model calculation methods, this invention significantly reduces the computational load. Compared with single correlation regression prediction methods, it has better accuracy and adaptability, and has broad practical application value.