【作者】 王春生； 吴敏； 曹卫华；

【Author】 Wang Chunsheng,Wu Min,Cao Weihua School of Information Science and Engineering,Central South University,Changsha 410083,China

【机构】 中南大学信息科学与工程学院；

【摘要】 针对传统铅锌烧结配料方法成本高和准确率低的问题,提出基于烧结块成分集成预测模型与专家推理策略的烧结配料优化综合集成方法。首先,在建立专家经验机理模型和神经网络模型的基础上,提出了一种既可保证预测精度又能满足配料计算对数据完备性要求的铅锌烧结块成分预测智能集成模型;其次,以成本最小为目标建立烧结配料优化模型,采用专家推理优化策略和定性定量综合集成方法,将上述模型综合集成,从而实现烧结配料的优化,仿真结果验证了该方法的有效性。更多还原

【Abstract】 To deal with the problem of high cost and low accuracy existed in traditional methods of lead-zinc sinter mix pro-portions,a methodology based on integrated prediction models of agglomerate composition and expert reasoning strategies is proposed in this paper.First,based on the expert experience mechanism model and neural network model,an intelligent inte-grated model is presented to assure the composition prediction precision of Pb-Zn agglomerate and to meet the requirements of the data completeness by blending computation.Then,the sinter proportion optimization model is established with the ob-jective of minimizing the costs.Finally,the proportions are optimized through expert reasoning optimization strategies and an integrated synthesis methodology.The simulation results demonstrate the validity of this methodology.更多还原