Design method for multi-target cooperative sampling scheme of randomly-distributed geographic elements

A technology of geographical elements and sampling schemes, applied in the field of multi-objective collaborative sampling scheme design, can solve problems such as difficulty in setting optimal values, difficulty in obtaining weight values ​​of weighted average method, and failure to search for optimal solutions, etc., so as to save on-site Sampling cost, strong self-learning ability, and the effect of improving design efficiency

Active Publication Date: 2012-07-04
WUHAN UNIV
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Problems solved by technology

However, the above-mentioned traditional methods have certain deficiencies. For example, it is difficult to obtain the weight of the weighted average method for complex multi-objective problems, and the set weights usually lead to extreme situations where some objectives are optimal while others are poor; the minimum T

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  • Design method for multi-target cooperative sampling scheme of randomly-distributed geographic elements
  • Design method for multi-target cooperative sampling scheme of randomly-distributed geographic elements
  • Design method for multi-target cooperative sampling scheme of randomly-distributed geographic elements

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[0059] The theoretical basis involved in the present invention is as follows:

[0060] The design of a multi-indicator collaborative sampling scheme needs to meet two conditions: (1) the sample size and sample point layout of the sampling can make the kriging interpolation results of any index meet the minimum precision requirements; (2) the sampling method must be quantifiable ( Vasat et al., 2010). It can be seen that the spatial collaborative sampling of multiple indicators of physical geographic elements belongs to the category of multi-objective optimization problems. In the sampling process, the precision limit of each indicator is an optimization goal. Due to the different spatial distribution structures of the indicators, these optimization goals cannot be simultaneously satisfied in the same set of sample layout schemes. The contradiction between optimization objectives is manifested in the fact that when the sample plan optimizes the sample fitting accuracy of one i...

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Abstract

The invention relates to a design method for a multi-target cooperative sampling scheme of randomly-distributed geographic elements, which includes the steps: 1 selecting multiple geographic elements with random distribution characteristics as sampling targets, and acquiring pre-sampling sample point data of the targets; 2 exploring spatial variation structures of the pre-sampling data by an ordinary Kriging method, fitting and generating a theory semi-variable function of each target, and obtaining a spatial distribution integral of all the targets by a Gaussian sequential random simulation method according to the theory semi-variable functions and the pre-sampling sample point data in the step 1; 3 computing the minimum cooperative sample size according to the precision requirements of the targets and prior variance, and setting a cooperative particle swarm optimization parameter; and 4 optimizing a current pre-sampling sample point scheme by means of cooperative particle swarm optimization, so that the multi-target cooperative sampling scheme is obtained. By the aid of the method, on-site sampling cost can be saved, self-organization and optimization during distribution of thesampling sample points are improved, and the design efficiency of the multi-target cooperative sampling scheme of the geographic elements is enhanced.

Description

technical field [0001] The invention relates to a method for designing a multi-objective cooperative sampling scheme, in particular to a method for designing a multi-objective cooperative sampling scheme for randomly distributed geographic elements. Background technique [0002] Geographic elements include topography, climate, hydrology, biology, and soil. Accurate surveys of them are the key to explaining the spatial distribution and evolution of geographic elements, and are also required for resource management, disaster management, ecological environment governance, and global change research. In the actual operation process, in order to save sampling cost and improve sampling efficiency, researchers usually only design a set of sampling plan to implement the spatial sampling survey task of multiple geographical element indicators at the same time, so how to design a sampling plan to ensure the sampling accuracy of multiple indicators becomes a focus of scholars' attentio...

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Application Information

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IPC IPC(8): G06F17/30G06N3/00
Inventor 刘耀林刘殿锋刘艳芳赵翔
Owner WUHAN UNIV
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