Fuzzy logic-based continuous Hopfield network for economic dispatch
Continuous Hopfield networks (CHNs) have been extensively employed as neural models for constrained optimization problems due to their parallel computing capabilities and fast convergence properties. Nevertheless, given their reliance on rigid weight and bias parameters, their scalability in dynamic and volatile situations remains limited. To address this limitation, we introduce a CHN based on fuzzy logic (Fuzzy CHN), where fuzzy inference schemes actively tune weights and biases according to real-time feedback. This adaptive setting enhances flexibility, convergenc