Researchers are exploring the use of various algorithms and models for storm prediction, including lstm and xgboost. Other approaches being investigated include swarm-based deep neural networks, ensemble models, and neural networks combined with wavelet transformation and optimization algorithms. The effectiveness of different machine and deep learning models is being compared, particularly in relation to high stationarity data and specific conductance data reconstruction.