Late Quaternary tectonics, sea-level change and lithostratigraphy along the northern coast of the South China Sea

2015 ◽  
Vol 429 (1) ◽  
pp. 123-136 ◽  
Author(s):  
Y. Zong ◽  
G. Huang ◽  
X. Y. Li ◽  
Y. Y. Sun
2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Shanwei Liu ◽  
Yue Jiao ◽  
Qinting Sun ◽  
Jinghui Jiang

The South China Sea is China’s largest marginal sea area, and it is rich in oil and gas mineral resources; thus, estimating its sea level changes is of practical significance. Based on linear and nonlinear sea level change characteristics, this paper decomposes 1992–2019 monthly mean sea level anomaly time series in the South China Sea into trend, seasonal, and random terms. This paper compares the seasonal autoregressive integrated moving average (SARIMA) and Prophet models for estimating the trend and seasonal terms and the long short-term memory (LSTM) and radial basis function (RBF) models for estimating random terms, and the more suitable models were selected. A Prophet-LSTM combined model was developed based on the accuracy results. This paper uses the combined model to study the effect of known data length on the experimental results and determines the best prediction duration. The results show that the combined model is suitable for short-term and medium-term estimations of 12–36 months. The accuracy at 36 months is 0.962 cm, which proves that the combined model has high application value for estimating sea level changes in the South China Sea.


2017 ◽  
Vol 36 (1) ◽  
pp. 9-16 ◽  
Author(s):  
Hui Wang ◽  
Kexiu Liu ◽  
Zhigang Gao ◽  
Wenjing Fan ◽  
Shouhua Liu ◽  
...  

2021 ◽  
Vol 584 ◽  
pp. 110673
Author(s):  
Yinqiang Li ◽  
Kefu Yu ◽  
Lizeng Bian ◽  
Yeman Qin ◽  
Weihua Liao ◽  
...  

2013 ◽  
Vol 111 ◽  
pp. 88-96 ◽  
Author(s):  
Xiang Su ◽  
Chuanlian Liu ◽  
Luc Beaufort ◽  
Jun Tian ◽  
Enqing Huang

2019 ◽  
Vol 38 (11) ◽  
pp. 111-120
Author(s):  
Peng Xia ◽  
Xianwei Meng ◽  
Zhen Li ◽  
Pengyao Zhi ◽  
Mengwei Zhao ◽  
...  

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