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The Prediction and Classification of Vespa Mandarinia Based On LSTM and Decision Tree

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DOI: 10.23977/erej.2021.050106 | Downloads: 1 | Views: 70

Author(s)

Cheng Yi 1

Affiliation(s)

1 Tongji University, Shanghai, 200082

Corresponding Author

Cheng Yi

ABSTRACT

As it know that Vespa mandarinia hunt bees and other natural creatures in large quantities, and its venom is very harmful to the human body. Once discovered in the United States, they attracted widespread attention from relevant departments and the public.In view of this situation, this article aims to solve these five problems: The first problem is to predict and analyze the spread of the Vespa mandarinia. The second problem is to establish a model based on the providing information to analyze whether the witnesses misclassified or not. The third problem is to carry out a quantitative analysis of the priority processing order of the report on the basis of the second model. The fourth problem is to use statistics to analyze the update time of the model. The last question is to judge whether the Vespa mandarinia is eradicated or not according to the model and providing data.

KEYWORDS

Vespa mandarinia, the Asian giant hornet, LSTM, CNN, rating, level, Decision Tree, classification

CITE THIS PAPER

Cheng Yi, The Prediction and Classification of Vespa Mandarinia Based On LSTM and Decision Tree. Environment, Resource and Ecology Journal (2021) 5: 37-45. DOI: http://dx.doi.org/10.23977/erej.2021.050106

REFERENCES

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