摘要
烧结工序能耗预测与优化研究是确保生产有序合理、节能环保和低成本的重要手段。在烧结工序能耗定义分析及烧结工序能耗主要影响因素分析的基础上,建立了基于径向基神经网络-遗传算法(RBF—GA)的烧结能耗预测与优化模型。在神经网络模型对能耗高精度预报的基础上结合遗传算法求解优化模型,计算出最佳的输入参数组合。通过案例研究,验证了所提方法的正确性和有效性。
Study on prediction and optimization of sintering process energy consumption is an important way to ensure smooth production, energy conservation and environmental protection and low cost. On the basis of the definition analysis of sintering process energy consumption and the analysis of its major influencing factors, the sintering energy consumption prediction and optimization model based on RBF--GA was established. Based on the high-accuracy prediction of neural network model and in combination with model solving by GA, the best input parameters combination was calculated. A case example was provided to verify the correctness and validity of the method.
出处
《烧结球团》
北大核心
2012年第6期13-17,共5页
Sintering and Pelletizing
基金
国家自然科学基金(70971102)
湖北省高等学校优秀中青年团队计划项目(T201102)
教育部人文社会科学研究项目(09YJC630182)
关键词
烧结
能耗
预测
优化
RBF—GA模型
sintering
energy consumption
prediction
optimization
RBF - GA model
