Extraction method for influence factors of carbon exchange of ecosystem and system

Abstract

The invention discloses an extraction method for influence factors of carbon exchange of an ecosystem and a system. The extraction method includes steps of 1), acquiring attribute data of carbon flux samples in a carbon flux data observation station; 2), inputting the attribute data, which are obtained in the step 1), of the carbon flux samples, selecting the optimal combination by the aid of proposed fuzzy rough and reduction integrated algorithm of shuffled frog leaping or quick fuzzy rough and reduction integrated algorithm based on importance, and finding an environmental factor set with the closest relationship with carbon flux; and 3), realizing modeling and stimulating for various environmental factors in the environmental factor set obtained from the step 2) by the aid of a neural network, and obtaining extraction rate of the environmental factors of the carbon flux. The extraction system comprises a data import module, a factor extraction module, an input module and an evaluation module. By the aid of the extraction method and the system, the range of correlation factors of the carbon flux in the researched ecosystem can be effectively reduced, research efficiency is improved, and inherent law among the environmental factors is found.

Description

technical field [0001] The invention relates to the technical field of data mining and fuzzy rough sets, in particular to a method and system for extracting factors affecting carbon exchange in an ecosystem. Background technique [0002] The study of atmospheric carbon dioxide is related to the sustainable development of human beings and the understanding of the laws between ecosystems. At present, the carbon flux data are obtained by setting up observatories and carbon towers in various ecosystems at home and abroad. However, due to the high cost of carbon towers and their susceptibility to environmental and instrument failures, they cannot be widely promoted. Moreover, only by mining the relationship between various environmental and meteorological factors and carbon fluxes from carbon flux observation station data and remote sensing data, can it be possible to use remote sensing images and ground weather station data to study regional and even global carbon fluxes. Quant...

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Problems solved by technology

In terms of data analysis, at home and abroad, most of them rely on statistical methods to conduct regression analysis or statistical analysis on environmental factors that ecologists consider important. The defect is that they rely on experience to analyze individual attributes, which lacks comprehensiveness and tends to ignore important laws; although, In recent years, some scholars have used artificial intelligence methods to study the laws and patterns of carbon flux, but they have focused on the prediction of carbon flux, and have not conducted in-depth analysis from the perspective of environmental factors affecting carbon flux. As a result, the prediction model is complicated, and it is difficult to discover the internal laws; in addition, it is impossible to conduct a unified analysis of the carbon flux attribute data of different ecosystems, and it is also a deficiency at this stage to find the similarities and differences of each

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