Abstract
Biological invasion is a very common phenomenon. All alien species must have sites to grow and reproduce, which allows them to be called “colonizer” in a general sense. They would have adverse effects on the agricultural ecosystem by reducing the growth and output of the desired species.
In this case, the invasion of wasps caused serious potential adverse effects on bee populations in Europe, as well as on the other local biological populations. To reduce this adverse effect, avoiding invalid identify and reducing the possibility of the biological invasion, we construct model to identify wasps.
In this paper, we use Grey Forecast Model and Convolution Neural Network Model to improve the accuracy of identification and better control the disaster
In this case, the invasion of wasps caused serious potential adverse effects on bee populations in Europe, as well as on the other local biological populations. To reduce this adverse effect, avoiding invalid identify and reducing the possibility of the biological invasion, we construct model to identify wasps.
In this paper, we use Grey Forecast Model and Convolution Neural Network Model to improve the accuracy of identification and better control the disaster
| Original language | English |
|---|---|
| Journal | International Journal of Computer Science and Information Security |
| Volume | 19 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 2021 |