Multiple neural networks fusion model based on Choquet fuzzy integral
Xizhao Wang, Junfen Chen · 2005
It is well recognized that the fuzzy measure plays a crucial role in fusion of multiple different classifiers using fuzzy integral. Many papers have focused on how to determine a fuzzy measure. Taking into account the intuitive idea that every classifier has different classification ability to the different class and the important role of the fuzzy integral in the process of information fusion, This work presents an optimization problem. By solving this optimization problem, the density function can be determined. Our study focuses on the Choquet fuzzy integral and the g-Lamda fuzzy measure. It shows that, in comparison with other fuzzy integrals such as Sugeno integral, the Choquet fuzzy integral and the corresponding g-Lamda fuzzy measure have the better performance for the system classification accuracy.