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Research on Honeycomb Location and Dissemination Based on Cluster Analysis and Multivariable Probability Prediction

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DOI: 10.23977/erej.2021.050306 | Downloads: 10 | Views: 919

Author(s)

Yiming Liu 1, Yimin Yu 2, Chenhang Ding 2, Yifan Liu 1

Affiliation(s)

1 Faculty of Maritime and Transportation, Ningbo University, Ningbo, Zhejiang, 315832, China
2 Faculty of YANGMING, Ningbo University, Ningbo, Zhejiang, 315211, China

Corresponding Author

Yifan Liu

ABSTRACT

Asian giant hornets are extremely toxic and have an aggressive impact on local bee species. If the spread of Asian giant hornet is not predicted as early as possible and appropriate countermeasures are made, it will cause immeasurable losses. We predict the spread of the Asian giant hornet. Considering that the farthest movement axis of the Asian giant hornet is 5 km, it can be set as the constraint condition to achieve hierarchical clustering of the sighting positions. Therefore, based on the assumption that the Asian giant hornets in the same nest are grouped into a cluster, a yearly time-step probabilistic prediction model is built to estimate the possible nest coordinates.

KEYWORDS

Honeycomb Location, Cluster Analysis, Multivariable Probability Prediction

CITE THIS PAPER

Yiming Liu, Yimin Yu, Chenhang Ding, Yifan Liu. Research on Honeycomb Location and Dissemination Based on Cluster Analysis and Multivariable Probability Prediction. Environment, Resource and Ecology Journal (2021) 5: 24-27. DOI: http://dx.doi.org/10.23977/erej.2021.050306

REFERENCES

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[2] Zixiang Fei, Erfu Yang, David Day-Uei Li, et al. Deep convolution network based emotion analysis towards mental health care. 2020, 388:212-227.
[3] Ala’raj Maher, Majdalawieh Munir, Nizamuddin Nishara. Modeling and forecasting of COVID-19 using a hybrid dynamic model based on SEIRD with ARIMA corrections. 2021, 6:98-111.

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