Soft Computing in Engineering
- 204 Seiten
- 8 Lesestunden
Neural networks and genetic algorithms leverage nature-inspired problem-solving strategies, contrasting with traditional mathematical computing methods. These approaches excel in addressing complex inverse problems by focusing on reducing disorder, making them particularly effective in fields like computational mechanics and earthquake engineering. The book explores how these innovative techniques can enhance engineering solutions and improve understanding of complex systems.
