High-precision curve modeling intelligent method and device

Abstract

The invention relates to a high-precision curve modeling intelligent method and a high-precision curve modeling intelligent device. The high-precision curve modeling intelligent method comprises the following steps of: building geographical coordinate information of sampling points and variable sampling values to be detected; dispersing regional spaces to be detected into grid points, and building sampling equations; carrying out high-order difference dispersion on systems of partial differential equations represented by a first fundamental quantity and a second fundamental quantity, and obtaining dispersion equation sets; randomly selecting iterative initial value of high-precision curve modeling equation sets; adopting a preset conjugate gradient method to solve the high-precision curve modeling equation sets, and judging whether solving results are constricted or not; and further judging whether the solution of the high-precision curve modeling equation sets meets a Gauss-Codazzi equation set or not, and outputting a high-precision stimulated curve model relative to a variable to be detected. The high-precision curve modeling intelligent method and the high-precision curve modeling intelligent device perfect and develop the existing model, improve the model precision, give a model stopping criteria, solve a sensitive problem to an initial value, solve a boundary shaking problem generated in the former interpolation, and improve the interpolation precision in the boundary.

Description

technical field [0001] The invention relates to a curved surface modeling method in the fields of geosciences and computers, in particular to an intelligent method and device for high-precision curved surface modeling. Background technique [0002] Since the birth of the first digital ground model in the 1950s, surface modeling methods have developed rapidly. In the late 1960s, the error problem of surface modeling attracted the attention of relevant experts, and several error detection methods and improvement methods were produced. However, these methods have not considered the theoretical root of the error, and have certain limitations. In order to solve the error problem that has long plagued the fields of geographic information system (GIS) and computer-aided design (CAD) since the late 1960s, Yue Tianxiang and others pioneered the establishment of a high-precision surface modeling (HASM) method based on the basic theorem of surface theory. . [0003] High-precision s...

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Problems solved by technology

2. For the boundary oscillation problem of the simulation area, the boundary error problem of HASM has not been completely solved at present, and the simulation accuracy at the boundary is still low. Although it was previously proposed to simulate the boundary of the boundary with the Laplace equation to reduce the boundary error of the simulation zone influence, but the effect is not significant, and to a certain extent lacks theoretical basis

3. After repeated tests, it is found that there are individual cases that make the interpolation effect of the HASM model worse than that of the classical geostatistical method (Kriging method). It may be that HASM4 only considers the first two equations in formula (1), and discards the equations satisfied by the mixed partial derivative term. The main reason for the error of the HASM model is still unclear

4. Although the HASM model is based on the basic theorem of surface theory, its theoretical foundation is not yet complete. HASM4 is only based on a part of the basic theorem of surface theory, and cannot fully describe the content expressed by the basic theorem of surface theory.

It is difficult to set the number of iterations for different problems, and it is often difficult for users to judge whether the surface finally obtained by the HASM model is the required surface

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