Fireworks Algorithm in MATLAB

In the field of computer science, machine learning algorithms play a crucial role. Among these, a novel optimization algorithm based on fireworks explosion mechanisms can be studied and implemented. This algorithm employs population-based search strategies where solutions are represented as fireworks, and their explosion sparks generate new candidate solutions iteratively. Key MATLAB functions like randn for Gaussian distribution-based spark generation and fitness evaluation for selection processes are central to its implementation. By leveraging this algorithm, researchers can enhance data processing capabilities in domains like data mining and artificial intelligence, leading to more informed decision-making. The MATLAB code typically involves initializing firework positions, calculating explosion amplitudes, generating sparks with adaptive diversity control, and selecting optimal candidates through elitism strategies. Mastering this algorithm enables more efficient utilization of computational resources, improving both workflow accuracy and scalability while opening new possibilities for future technological advancements.