Trajectory tracking of Asian giant hornets based on SVM and BA-SVM algorithm

Shi-fan Chen; Yang Yang; Yu-shun Xia; HanTing Guo

doi:10.1117/12.2638762

17 May 2022 Trajectory tracking of Asian giant hornets based on SVM and BA-SVM algorithm

Shi-fan Chen, Yang Yang, Yu-shun Xia, HanTing Guo

Proceedings Volume 12259, 2nd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2022); 1225961 (2022) https://doi.org/10.1117/12.2638762
Event: 2nd International Conference on Applied Mathematics, Modelling, and Intelligent Computing, 2022, Kunming, China

Abstract

Taking the Asian Giant Hornets invasion encountered by Washington in 2019 as an example, this paper uses algorithms such as SVM and Cellular Automaton to build models from multiple perspectives, such as bumblebee propagation patterns, identification and classification of sighting reports, and prediction of future occurrences. Building the spacetime influence domain network model to analyze the basic laws of propagation, it is concluded that the propagation is mainly limited by time and location. The cellular automata model is used to study the propagation path from time, space and state, and the propagation path is obtained. It presents a characteristic that the center diverges to both sides; the neural network model is established to predict that under the premise of accuracy R≈1, its future appearance will be near “Kendall”. The SVM binary classification model is constructed, and the accuracy of the K test is AUC=0.79, which can accurately classify the authenticity of eyewitness reports. The model is updated based on the BA-SVM algorithm, and the accuracy will increase in the future. Based on multivariate Gaussian fitting, under the fitting effect of RSquare=0.9612 and 0.9073, the update frequency of sighting reports can be kept low. This paper aims to provide better solutions for species invasion research using machine learning.

Citation Download Citation

Shi-fan Chen, Yang Yang, Yu-shun Xia, and HanTing Guo "Trajectory tracking of Asian giant hornets based on SVM and BA-SVM algorithm", Proc. SPIE 12259, 2nd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2022), 1225961 (17 May 2022); https://doi.org/10.1117/12.2638762

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KEYWORDS

Data modeling

Eye models

Detection and tracking algorithms

Neural networks

Statistical analysis

3D modeling

Algorithm development

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