Prediction of alpine meadow degradation in the source of Sanjiangyuan area based on the K-means and DNN fusion model

Chunmei Li; Yihan Ma; Zhehao Zhang; JieTeng Jiang; Yunpeng Jin; Kai Li; Haiyang Li

doi:10.1117/12.2641361

10 November 2022 Prediction of alpine meadow degradation in the source of Sanjiangyuan area based on the K-means and DNN fusion model

Chunmei Li, Yihan Ma, Zhehao Zhang, JieTeng Jiang, Yunpeng Jin, Kai Li, Haiyang Li

Author Affiliations +

Proceedings Volume 12348, 2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2022); 123480N (2022) https://doi.org/10.1117/12.2641361
Event: 2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2022), 2022, Zhuhai, China

Abstract

Alpine meadow in Sanjiangyuan area plays an important role in the ecological situation of China. However, in recent years, the grassland vegetation in this area has been seriously degraded due to the impact of climate and human activities. Reasonable prediction of grassland degradation is a prerequisite to protect the ecological environment of the area, but the traditional manual measurement method is time-consuming and inefficient. Specifically, in order to solve the problem of data shortage, we first spent 2-3 months on-the-spot measurement to obtain more than 150,000 pieces of data for supervised learning, and divided them into training sets and test sets. In the training phase, the DNN model and K-mean algorithm are used to preprocess the data in parallel, and then the trained model is used to predict, which greatly shortens the test time. Finally, several experiments are carried out in the test set to verify the validity of the model. The average prediction accuracy is more than 99%, and AUC index is more than 95%. It is indirectly proved that the model can be applied to the prediction of grassland vegetation degradation in Sanjiangyuan area.

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Chunmei Li, Yihan Ma, Zhehao Zhang, JieTeng Jiang, Yunpeng Jin, Kai Li, and Haiyang Li "Prediction of alpine meadow degradation in the source of Sanjiangyuan area based on the K-means and DNN fusion model", Proc. SPIE 12348, 2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2022), 123480N (10 November 2022); https://doi.org/10.1117/12.2641361

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Data modeling

Neural networks

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