Explore MATLAB source code curated for "蝙蝠算法" with clean implementations, documentation, and examples.
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.
Intelligent Optimization Algorithm - Bat Algorithm Implementation
Professor Xinshe Yang's source code implementation of the Bat Algorithm from Cambridge University, featuring optimization algorithm implementation details
Implementation of Bat Algorithm-Optimized Relevance Vector Machine for Accurate Data Modeling and Prediction
Implementation of bat algorithm in MATLAB, utilizing several common benchmark test functions to evaluate convergence speed and solution accuracy.
The Bat Algorithm is a meta-heuristic optimization algorithm developed by Xin-She Yang in 2010. This algorithm is inspired by the echolocation behavior of microbats, which utilize varying emission rates and loudness of pulses for navigation and prey detection.
MATLAB implementation of the innovative Bat Algorithm for production optimization problems, featuring swarm intelligence techniques and adaptive parameter control
Implementing the Bat Algorithm to Optimize Functions with Code-Level Descriptions
Implementation of Bat Algorithm for Parameter Optimization in Backpropagation Neural Networks
Implementation of Bat Algorithm for Optimizing Extreme Learning Machine Parameters