In today's rapidly changing world, improving forecast accuracy is more crucial—and more challenging—than ever. Traditional methods struggle to keep up with unpredictable consumer behavior, driven by ...

Researchers in China conceived a new PV forecasting approach that integrates causal convolution, recurrent structures, attention mechanisms, and the Kolmogorov–Arnold Network (KAN). Experimental ...

Soft measurement based on data-driven models is widely used to predict key variables in process industry due to low cost and real-time capability. However, these models struggle with noisy datasets ...