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Training data processing method for evaluating grassland degeneration degree

A technology of degradation degree and training data, applied in the field of training data processing for evaluating grassland degradation degree, it can solve problems such as being too simple and low in applicability, and achieve the effect of strong generality and objective and accurate evaluation of grassland degradation degree.

Inactive Publication Date: 2019-09-20
QINGHAI UNIVERSITY
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  • Abstract
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Problems solved by technology

The impact of grassland degradation on the environment is particularly severe. The existing methods for collecting and processing grassland degradation information are too simple and have low applicability

Method used

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  • Training data processing method for evaluating grassland degeneration degree
  • Training data processing method for evaluating grassland degeneration degree
  • Training data processing method for evaluating grassland degeneration degree

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Experimental program
Comparison scheme
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Embodiment

[0021] Data source introduction: Sanjiangyuan alpine meadow, as a unique grassland type, has become the research object of many researchers.

[0022] Specific implementation scheme: a kind of training data processing method that is used to evaluate the degree of degradation of grassland, the existing data is used as the parameter set of neural network, this parameter set is classified according to the degree of degradation of grassland, that is, non-degraded, slightly degraded, Moderately degraded, severely degraded and extremely degraded, and then establish a neural network model, and then collect and arrange the visible grassland vegetation data on the grassland to be evaluated as a training set, and compare and analyze the training set and parameter set through the neural network model, To obtain the degree of degradation of the grassland to be evaluated, the parameter set is formatted using the formula minimum and maximum normalization, and the minimum and maximum normaliza...

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Abstract

The invention relates to the technical field of grassland degradation improvement. Specifically, the invention relates to a training data processing method for evaluating the grassland degeneration degree. Existing data is used as a parameter set of the neural network; the parameter set is classified according to the grassland degradation degree, namely no degradation, light degradation, medium degradation, heavy degradation and extreme degradation exist; a neural network model is established, visual grassland vegetation data on the grassland to be evaluated are collected and arranged as a training set; through the neural network model, the training set and the parameter set are compared and analyzed; according to the grassland degeneration degree evaluation method, collected mass data can be scientifically processed and summarized, some error and unnecessary data are removed, the remaining high-quality data are analyzed, and experts are assisted to scientifically evaluate the grassland degeneration degree to be evaluated.

Description

technical field [0001] The invention relates to the technical field of grassland degradation improvement, in particular to a training data processing method for evaluating grassland degradation degree. Background technique [0002] In the era of big data, a large amount of data is generated in various fields every day. If these data cannot serve human beings, they may become useless data or even garbage. However, when we make good use of these big data, it may turn waste into treasure. The Qinghai region, located on the Qinghai-Tibet Plateau, the roof of the world, is the hinterland of the source of the three rivers, the birthplace of the Yangtze River, the Yellow River, and the Lancang River. The climate here will affect the climate in the middle and lower reaches of the Yangtze River, the Yellow River, and even central and South Asia. Therefore, Sanjiangyuan ecological protection is one of the country's important strategies, and a lot of money has been invested over the y...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/04G06N3/08G06K9/62
CPCG06N3/084G06N3/045G06F18/241
Inventor 李春梅刘志强欧为友肖锋杨新存田芳周钧马蓉
Owner QINGHAI UNIVERSITY
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