Absolute neuro-fuzzy classification of remote sensing data

Abstract

Hybrid intelligent systems are discussed. These systems combine neural networks, which recognize patterns and adapt themselves to cope with changing environments, and fuzzy inference systems that incorporate human knowledge and perform inferencing and decision making. The integration of these complimentary techniques along with derivative-free optimization techniques based on genetic algorithms, results in a novel discipline called neuro-fuzzy and soft computing. These approaches are discussed and applied in classification of multisource remote sensing and geographic data. Both the rationale of the approaches and the results obtained are compared to more traditional techniques.