Land system change causal structure recognition method, system and device

An identification method and causal relationship technology, applied in the field of environmental modeling, which can solve the problems that correlation analysis cannot identify cause and effect, violate the complexity of the land system, and cannot identify the causal structure of land system changes.

Inactive Publication Date: 2018-11-23
GUANGDONG INST OF ECO ENVIRONMENT & SOIL SCI
View PDF7 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The limitations of these statistical models are: (1) correlation analysis cannot identify causality, and these statistical models based on correlation analysis cannot identify the causal structure of land system changes; (2) these models assume that the independent variables of the model are

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Land system change causal structure recognition method, system and device
  • Land system change causal structure recognition method, system and device
  • Land system change causal structure recognition method, system and device

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0042] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0043] refer to figure 1 , a method for identifying a causal structure of a land system change, comprising steps S100, S200 and S300.

[0044] Before performing the following steps, the assumptions of the model need to be set artificially. The assumptions of the model include: (1) the model variables satisfy the normal distribution; (2) in order to ensure the validity of the data, we need to set a significant sex level value. Usually take α<0.05 or α<0.01. This shows that there is a 95% or 99% chance (probability) that their model is correct.

[0045] S100. Obtain the data of land use type change and the data of influencing factors in several time periods in the research area.

[0046] For example, collect data on changes in land use types and related influencing factors from 2005 to 2010. The influencing factors can be natural environment...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a land system change causal structure recognition method, system and device. The method comprises the following steps: land use type change data and influencing factor data ina plurality of time periods in a study area are acquired; with the land use type change data and the influencing factor data as model variables, a causal structure network is constructed; and a causalrelationship between the model variables in the causal structure network is recognized based on a PC algorithm, and a causal graph model is obtained. The relationship between the land use type changes and the influencing factors in the study area is considered comprehensively, the PC algorithm is used to recognize the causal relationship between the model variables in the causal structure network, and the causal structure among the land system variables can be effectively recognized; the method can integrate changes of each land use type in the land system and each factor influencing the landsystem changes between different systems and the complexity characteristic of the land system is better met; and the method can be widely applied to the field of environmental modeling.

Description

technical field [0001] The invention relates to the field of environmental modeling, in particular to a method, system and device for identifying the causal structure of land system changes. Background technique [0002] Land is the carrier of human survival and an important natural resource that supports human production and life. The land system involves multiple factors such as society, economy, and ecological environment, and is closely related to multiple global focal issues such as population, resources, food security, and the environment. At a time when global change is facing severe challenges, through in-depth and detailed research on the causal structure and interaction of man-land coupling systems, the development of land system theory and applications will be promoted to provide in-depth thinking for global change research. [0003] The land system is a dynamic system formed by the interaction between man and land, so in essence, changes in the land system basic...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06Q10/06G06Q50/26
CPCG06Q10/067G06Q50/26
Inventor 王琦
Owner GUANGDONG INST OF ECO ENVIRONMENT & SOIL SCI
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products