Fluctuation Analysis

Fluctuation analysis examines variability in data across diverse fields, aiming to understand the underlying processes generating these fluctuations and extract meaningful information from them. Current research focuses on applying this to diverse areas, including fault detection in industrial processes (using encoder-based models), predicting outcomes in dynamic systems like sports matches (employing XGBoost and LSTM networks), and optimizing processes with inherent stochasticity (leveraging Bayesian optimization). These analyses provide valuable insights for improving system reliability, enhancing predictive modeling, and optimizing complex processes across various scientific and engineering domains.