On hierarchical cloud inference system with uncertainty and its universal approximation performance
Zhu Feng · Computer Engineering and Applications Journal · 2011
In order to solve the problem that the number of rules in intelligent control and prediction based on cloud model increases exponentially with the number of variables involved,a hierarchical cloud inference system with uncertainty is proposed and its approximation performance is testified.The hierarchical cloud inference system with uncertainty is constructed using the new reasoning model about uncertainty based on cloud theory and analytical expression is given,then the capability of the hierarchical cloud inference system with uncertainty approximating any continuous function on a compact set is testified.The result shows the computational expression of output results of the hierarchical cloud inference system with uncertainty satisfies the three hypothetic conditions of Stone-Weirstrass theorem and the system has global approximation property.