Hongqing Wang

Aug 30, 2024 | pubs.usgs.gov | Ling Zhu |Hongqing Wang |Qin Chen |William D. Capurso

First posted August 30, 2024 The Shinnecock Indian Nation on Long Island, New York, faces challenges of shoreline retreat, saltwater intrusion, and flooding of the Tribal lands under changing climate and rising sea level. However, understanding of the dynamics of tidal circulation and waves and their impacts on the Shinnecock Indian Nation’s shoreline remains limited.

Aug 23, 2023 | mdpi.com | Hongqing Wang |Lifu Zhang |Rong Wu |Hongying Zhao

4. Results and Discussion 4.1. Performance Analysis and Model ComparisonIn this section, we provide a detailed comparison of our proposed model, MegaTT, with a series of established benchmark models extensively utilized in the field of environmental data prediction. For the sake of transparency, reproducibility, and fairness in our experimental setup, each model’s specific architectural configurations and principal parameters are comprehensively explained.

Aug 16, 2023 | mdpi.com | Hongqing Wang |Lifu Zhang |Rong Wu

4.2. Models Comparation and Performance AnalysisIn order to establish the efficacy of the proposed MSAFormer model, it was juxtaposed against five widely recognized models: Support Vector Machine (SVM) [30], Random Forest (RF) [32], Adaptive Boosting (AdaBoost) [34], Long Short-Term Memory (LSTM) [43], and Gated Recurrent Unit (GRU) [46]. These models are detailed below:Support Vector Machine (SVM): This was implemented employing a radial basis function (RBF) kernel.