MATLAB Intelligent Algorithm Implementation: 30 Case Studies

In "MATLAB Intelligent Algorithm Implementation: 30 Case Studies," the author demonstrates intelligent algorithm applications through comprehensive case studies. The book provides detailed explanations and MATLAB implementations for fundamental intelligent algorithms including Genetic Algorithms (for optimization problems), Immune Algorithms (pattern recognition), Simulated Annealing (global optimization), Particle Swarm Optimization (PSO for multi-dimensional search), Artificial Fish Swarm Algorithm (AFSA for collective behavior simulation), Ant Colony Optimization (ACO for path planning), and Neural Network Algorithms (pattern recognition and prediction). Each case study includes practical MATLAB code examples demonstrating algorithm initialization, parameter tuning, and convergence analysis. The content is structured to benefit both beginners learning algorithm fundamentals and researchers seeking advanced implementation techniques. Readers gain not only practical coding skills but also deep insights into algorithm strengths/weaknesses and selection criteria for specific application scenarios. The MATLAB implementations emphasize efficient coding practices, including vectorization techniques and algorithm parameter optimization strategies.