Hybrid artificial intelligence approach to urban planning

Knowledge-based modeling and implementation of the various urban planning p rocesses represent an intensive research area. This paper presents a hybrid artificial intelligence system using a knowledge-based approach neural net works and fuzzy logic that automates the decision-making process in urban p lanning. The system is used for developing urban development alternatives b ased on real-world data. Results show that. by integrating knowledge-based systems, artificial neural networks and fuzzy systems, the system achieves improvements in the implementation of each respective system as well as an increase in the breadth of functionality within the application. With this approach, the best of three technologies can be compiled together to solve complex urban problems. We discuss the structure of the combined technologi es, as It ell as providing examples of its application hr the field of urba n development.