To enhance the accuracy and convergence speed of electricity load forecasting, this paper proposes an optimized electricity load forecasting model that integrates a Modified Frilled Lizard Optimization (MFLO) algorithm with a Backpropagation (BP) neural network. The MFLO addresses the traditional challenges of slow convergence and local optima by incorporating Lévy flight mechanisms and self-weight factors, which enhance global search capabilities. By integrating information entropy into fitness adjustments, the model improves the quality of i...
