Supercharge Your Innovation With Domain-Expert AI Agents!

Ecosystem attribute component composition structure time evolution quantitative analysis method

An ecosystem and quantitative analysis technology, applied in data processing applications, instruments, forecasting, etc., can solve the problem of comparative analysis of time evolution laws of different ecosystem attribute components, lack of quantitative description, and difficult ecosystem attribute component structures Quantitative analysis of time evolution law and other issues

Pending Publication Date: 2021-03-26
BINZHOU UNIV +1
View PDF5 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, this method lacks a corresponding quantitative description, and it is difficult to carry out quantitative analysis on the time evolution law of the component structure of the same ecosystem attribute, and it is also difficult to conduct a comparative analysis on the time evolution law of the composition structure of different ecosystem attribute components

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
  • Ecosystem attribute component composition structure time evolution quantitative analysis method
  • Ecosystem attribute component composition structure time evolution quantitative analysis method

Examples

Experimental program
Comparison scheme
Effect test

specific Embodiment approach 1

[0013] Embodiment 1: The quantitative analysis method for the time evolution of the composition and structure of the ecosystem attribute components in this embodiment is carried out according to the following steps:

[0014] 1. Calculation of quantitative indicators of frequency parameters of attribute components: Obtain the multi-period frequency distribution data of the attribute components of the ecosystem, and calculate the quantitative indicators of frequency parameters respectively;

[0015] 2. Taking the quantitative index of each frequency parameter as the dependent variable and time as the independent variable, obtain the univariate linear regression time trend model of each frequency parameter, and form the parameter set of the trend model, and then learn the temporal evolution of the composition and structure of the ecosystem attribute components. .

specific Embodiment approach 2

[0016] Embodiment 2: The difference between this embodiment and Embodiment 1 is that the ecosystem attribute component in step 1 is a vegetation index or an ecological parameter. Other steps and parameters are the same as in the first embodiment.

specific Embodiment approach 3

[0017] Embodiment 3: The difference between this embodiment and Embodiment 1 or 2 is that the frequency parameter in step 1 includes the concentration value, average value, degree of change, degree of symmetry and degree of deviation of the frequency distribution of each period. Other steps and parameters are the same as in the first or second embodiment.

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 an ecosystem attribute component composition structure time evolution quantitative analysis method, and relates to an ecosystem attribute component composition analysis method.The method comprises the following steps of: 1, calculating attribute group frequency parameter quantitative indexes; and 2, respectively obtaining a unary linear regression time trend model of eachfrequency parameter by taking the quantitative index of each frequency parameter as a dependent variable and time as an independent variable, forming a trend model parameter set, and obtaining the time evolution condition of the ecosystem attribute component composition structure. According to the method, the time series data of the ecosystem attribute component frequency parameter quantitative indexes are utilized to construct the change trend mathematical model so as to quantitatively reflect the time evolution rule of the ecosystem attribute component composition structure, and the quantitative analysis of the time evolution of the ecosystem attribute component composition structure can be realized.

Description

technical field [0001] The invention relates to a method for analyzing the composition of ecological system attributes. Background technique [0002] At present, the graphic method is used to express the long-term evolution process of the composition and structure of the attribute components of the ecosystem, and the long-term evolution trend of the composition and structure of the attribute components of the ecosystem is visually displayed through the two-dimensional isoline distribution graph of the frequency of the attribute components. However, this method lacks the corresponding quantitative description, and it is difficult to quantitatively analyze the time evolution law of the attribute component structure of the same ecosystem, and it is also difficult to compare and analyze the time evolution law of the attribute component structure of different ecosystems. SUMMARY OF THE INVENTION [0003] The invention provides a method that can quantitatively describe the long-...

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): G06Q50/02G06Q10/06G06Q10/04
CPCG06Q50/02G06Q10/067G06Q10/04
Inventor 董凯凯陈子琦侯光雷刘兆礼
Owner BINZHOU UNIV
Features
  • R&D
  • Intellectual Property
  • Life Sciences
  • Materials
  • Tech Scout
Why Patsnap Eureka
  • Unparalleled Data Quality
  • Higher Quality Content
  • 60% Fewer Hallucinations
Social media
Patsnap Eureka Blog
Learn More