Persistent seed bank prediction method based on random forest

A random forest and prediction method technology, applied in the fields of botany and restoration ecology, can solve laborious and time-consuming problems, achieve the effects of saving manpower and time, saving costs, and improving research efficiency

Inactive Publication Date: 2017-01-04
LIAONING UNIVERSITY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

It can be seen that the determination of the persistent seed bank in the past needs to be established on the basis of experimental research, which has the disadvantages of time-consuming and laborious

Method used

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Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0021] The prediction method of persistent seed bank based on random forest, the steps are as follows:

[0022] 1) Collect plant seed traits and build a seed trait database;

[0023] 2) Collect the attributes of the plant persistent seed bank and build the database of the persistent seed bank;

[0024] 3) Using the species name as an associated item, associate the seed trait database with the persistent seed bank database;

[0025] 4) Randomly select data from the seed trait database and persistent seed database, delete the data with only seed traits or persistent seed bank information, and use the random forest algorithm to construct a training set;

[0026] 5) Establish a prediction model based on the training set, which has multiple decision trees, and implement classification according to the classification voting results of the decision trees;

[0027] 6) Select data that does not contain persistent seed bank information from the database associated with seed traits and...

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PUM

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Abstract

The invention relates to a persistent seed bank prediction method based on a random forest. A technical scheme is characterized by collecting or determining a plant seed trait and constructing a seed trait database; collecting or determining a plant persistent seed bank attribute and constructing a persistent seed bank database; associating the seed trait database with the persistent seed bank database; selecting parts of data from the database and using a random forest algorithm to construct a training set; based on the training set, establishing a prediction model; selecting data which does not associated with the persistent seed bank data from the seed trait database and establishing a prediction set; using the prediction model and the prediction set to predict; and according to a prediction result, determining whether a corresponding plant has a persistent seed bank. The method can be used to predict whether the plant seed has the persistent seed bank. Compared to an experiment method, the method in the invention is simple and easy, and manpower and time are saved.

Description

technical field [0001] The invention relates to the fields of botany and restoration ecology, in particular to a method based on a random forest algorithm for predicting whether there is a persistent seed bank in a plant species. It is an important means to understand the interaction between plants and the environment, and to promote vegetation restoration and species diversity protection. Background technique [0002] Persistent seed banks refer to seeds that have been in the soil for more than one year and still have the ability to germinate. Persistent seed bank is an important reproductive strategy for plants to adapt to the environment, especially harsh habitats. It is of great significance for understanding the interaction between plants and the environment, and the adaptation and evolution of plant species. [0003] Plants have developed a variety of reproductive strategies in the course of evolution, and the persistent seed bank is not a common reproductive strategy...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04
CPCG06Q10/04
Inventor 唐毅
Owner LIAONING UNIVERSITY
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