Optimizing Extreme Learning Machine (ELM) Input Weights and Biases Using the Bat Algorithm (BA)

Utilizing the Bat Algorithm (BA) to optimize Extreme Learning Machine (ELM) input weights and biases significantly improves diagnostic accuracy. This implementation involves iterative parameter tuning through BA's echolocation-inspired search mechanism, enhancing ELM's generalization capability via swarm intelligence optimization techniques.