Fourier-feature induced physics informed randomized neural network method to solve the biharmonic equation

Spatial heterogeneity of groundwater depths in coastal cities and their responses to multiple factors interactions by interpretable machine learning models

Scheduling automated guided vehicles considering the buffer lane constraints

Multi-Granularity Autoformer for long-term deterministic and probabilistic power load forecasting

Spatiotemporal variations of water levels and river-lake interaction in the Poyang Lake basin under the extreme drought

Classical and machine learning tools for identifying yellow-seeded Brassica napus by fusion of hyperspectral features

Editorial: Data-driven approaches for efficient smart grid systems

Robust autoregressive bidirectional gated recurrent units model for short-term power forecasting

Solving the temporal lags in local significant wave height prediction with a new VMD-LSTM model

Water resource forecasting with machine learning and deep learning: A scientometric analysis

Advancements in Q-learning meta-heuristic optimization algorithms: a survey

Analysis of fine-grained sediment dynamics from field observations with a vector autoregressive model

Probabilistic oil price forecasting with a variational mode decomposition-gated recurrent unit model incorporating pinball loss

Assessment and prediction of Water Quality Index (WQI) by seasonal key water parameters in a coastal city: application of machine learning models

Improving PID controller performance in nonlinear oscillatory automatic generation control systems using a multi-objective marine predator algorithm with enhanced diversity

Probabilistic quantile multiple fourier feature network for lake temperature forecasting: incorporating pinball loss for uncertainty estimation

Multiscale-integrated deep learning approaches for short-term load forecasting

Assessing and predicting water quality index with key water parameters by machine learning models in coastal cities, China

Pinball-Huber boosted extreme learning machine regression: a multiobjective approach to accurate power load forecasting

Solving a class of multi-scale elliptic PDEs by Fourier-based mixed physics informed neural networks