Ke-Cheng Peng
Affiliations:- National University of Defense Technology, College of Meteorology and Oceanography, Changsha, China
- National University of Defense Technology, College of Computer, Changsha, China
According to our database1,
Ke-Cheng Peng
authored at least 13 papers
between 2020 and 2024.
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Bibliography
2024
High-Resolution Remote Sensing of the Gradient Richardson Number in a Megacity Boundary Layer.
Remote. Sens., March, 2024
Validation of ERA5 Boundary Layer Meteorological Variables by Remote-Sensing Measurements in the Southeast China Mountains.
Remote. Sens., February, 2024
2023
Learning Rogue Waves of Nonlinear Schrödinger Equation with Enhanced Physics-Informed Neural Networks Simulator.
Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2023
Application of Improved Physics-Informed Deep Learning Based on Activation Function for Solving Nonlinear Soliton Equation.
Proceedings of the International Joint Conference on Neural Networks, 2023
Solving Localized Wave Solutions of the Nonlinear PDEs Using Physics-Constraint Deep Learning Method.
Proceedings of the Neural Information Processing - 30th International Conference, 2023
Surrogate Modeling for Soliton Wave of Nonlinear Partial Differential Equations via the Improved Physics-Informed Deep Learning.
Proceedings of the Advanced Intelligent Computing Technology and Applications, 2023
An Efficient Approximation Method Based on Enhanced Physics-Informed Neural Networks for Solving Localized Wave Solutions of PDEs.
Proceedings of the Artificial Neural Networks and Machine Learning, 2023
2022
Technology for Position Correction of Satellite Precipitation and Contributions to Error Reduction - A Case of the '720' Rainstorm in Henan, China.
Sensors, 2022
Position Error Correction for Satellite Precipitation Products Using Image Registration based on Unsupervised Learning.
Proceedings of the IEEE Smartworld, 2022
2021
Ensemble Empirical Mode Decomposition with Adaptive Noise with Convolution Based Gated Recurrent Neural Network: A New Deep Learning Model for South Asian High Intensity Forecasting.
Symmetry, 2021
Polar Vortex Multi-Day Intensity Prediction Relying on New Deep Learning Model: A Combined Convolution Neural Network with Long Short-Term Memory Based on Gaussian Smoothing Method.
Entropy, 2021
2020
El Niño Index Prediction Using Deep Learning with Ensemble Empirical Mode Decomposition.
Symmetry, 2020
Variational Principles for Two Kinds of Coupled Nonlinear Equations in Shallow Water.
Symmetry, 2020