Station network optimization method based on high-dimensional Copula entropy and Kriging

An optimization method and station network technology, applied in design optimization/simulation, stochastic CAD, ICT adaptation, etc., can solve problems such as the difficulty of describing the probability density function, the inability to evaluate the dynamic characteristics of station network optimization results, etc., to improve the efficiency of site optimization Effect

Pending Publication Date: 2022-06-07
YANGZHOU UNIV
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Problems solved by technology

[0005] Purpose of the invention: The present invention aims to provide a website network optimization method based on high-dimensional Copula entropy and kriging, to solve the difficulty and deficiency of the traditional website network evaluation method for

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  • Station network optimization method based on high-dimensional Copula entropy and Kriging
  • Station network optimization method based on high-dimensional Copula entropy and Kriging
  • Station network optimization method based on high-dimensional Copula entropy and Kriging

Examples

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Embodiment 1

[0110] Example 1: The dynamic rainfall station network composed of 43 stations in the Huai River Basin is optimized as a practical application

[0111] Taking the station network composed of 43 rainfall stations in the Huai River Basin as an example, taking the daily precipitation observation sequence from 1992 to 2018 as the research object, the station network is evaluated and optimized by the optimization method of the present invention.

[0112] (1) Overview of the river basin

[0113]The HuaiHe River Basin is located in the climate transition zone between the East Asian monsoon humid area and the sub-humid land zone, is the overlapping area of the three transition zones of north-south climate, high and low latitude and marine and continental facies, the weather system is complex and changeable, and the large-scale circulation and water vapor transport background also have a very significant impact on the climatic characteristics of the Huai River Basin, which is a "sensitive ...

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Abstract

The invention discloses a station network optimization method based on high-dimensional Copula entropy and Kriging. The method comprises the following steps: (1) constructing a hydrological C-Vine Copula tree structure; (2) estimating a C-Vine Copula parameter by adopting a maximum likelihood estimation method; (3) obtaining high-dimensional mutual information through a function relationship between the multivariable mutual information and the C-Vine Copula density; and (4) optimizing the dynamic rainfall station network through a standardized MiK-MiT-MaJ index and a sliding window method. According to the method, a high-dimensional dependency structure among multiple stations is obtained by adopting C-Vine Copula, and the total amount and the total correlation amount of station network objective function information are optimized; the optimal rainfall station network estimation error and the optimal rainfall information are realized by using the Kriging standard error value; multi-objective optimization is simplified into single-objective optimization, optimization efficiency is improved, and rainfall sequence time-varying characteristics are considered to cause dynamic characteristics of a station network optimization result.

Description

Technical field [0001] The present invention relates to a rainfall station network optimization method, in particular to a high-dimensional Copula entropy and kriging-based station network optimization method. Background [0002] The hydrometeorological station is a grass-roots hydrological institution set up on a river or river basin, which is mainly used to observe and collect hydrological and meteorological data related to rivers, lakes and reservoirs, and provides sufficient data support for the work of exploring the basic hydrological laws in the later stage through the complete collection and control of the actual measurement data in the early stage, and to a large extent meets the basic needs of hydrological forecasting, hydrological information, water resources evaluation work and water science research. Therefore, a well-planned hydrological station network can fully reflect the characteristics of hydrological spatio-temporal variation, so that it can collect accurate an...

Claims

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Application Information

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IPC IPC(8): G06F30/20G06Q50/26G06F111/08
CPCG06F30/20G06Q50/26G06F2111/08Y02A90/10
Inventor 徐鹏程仇建春李帆刘赛艳蒋新跃
Owner YANGZHOU UNIV
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