Title :
Intelligent modeling and optimization method based on comprehensive product indices for lead-zinc sintering process
Author :
Kai, Cui ; Weihua, Cao ; Min, Wu ; Chunsheng, Wang
Author_Institution :
Sch. of Inf. Sci. & Eng., Central South Univ., Changsha
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.
Keywords :
correlation methods; intelligent manufacturing systems; lead alloys; neural nets; particle swarm optimisation; principal component analysis; sintering; comprehensive product indices; gray correlation analysis; intelligent modeling; interconnected coupling; lead-zinc sintering process; multiobjective optimization technique; multiobjective particle swarm optimization algorithm; neural network prediction model; optimization method; principal components analysis; target function; Algorithm design and analysis; Centralized control; Information science; Lead; Network synthesis; Neural networks; Optimization methods; Particle swarm optimization; Predictive models; Production; Improved particle swarm; Lead-Zinc sintering process; Multi-objective optimization; Neural network; optimization algorithm;
Conference_Titel :
Control Conference, 2008. CCC 2008. 27th Chinese
Conference_Location :
Kunming
Print_ISBN :
978-7-900719-70-6
Electronic_ISBN :
978-7-900719-70-6
DOI :
10.1109/CHICC.2008.4605729