Intelligent modeling and optimization method based on comprehensive product indices for lead-zinc sintering process

Abstract

The lead-zinc sintering process has the characters of complex mechanism, multi-parameter and strong interconnected coupling. This paper presents an intelligent modeling and optimization method based on comprehensive production Indices. First, the neural network prediction model of the comprehensive production indices is proposed, which is synthesizing some techniques, including gray correlation analysis, principal components analysis, and neural network and so on. And the target function is deduced and the model based on comprehensive production Indices is given by using the multi-objective optimization technique. At last, this paper proposes an improved multi-objective particle swarm optimization algorithm based on SPEA2 to calculate the optimization executing parameters. The applied results of actual runs show that the intelligent modeling and optimization method proposed in this paper attains a better industrial effect, and provides an effective and new way to implement the global optimization.