摘要
焦炭是焦化企业生产的重要工业原料之一,准确地预测其未来价格趋势对焦化企业制定排产计划具有重要意义。极限学习机(ELM)泛化能力强,计算速度快,适合作为焦炭价格预测的模型,但ELM的预测性能受模型关键参数影响较大,故需对其参数进行优化。基于此,文中提出了基于双精英进化樽海鞘群算法的ELM焦炭价格预测方法。首先,采用Logistic混沌映射、改进的收敛因子、自适应惯性权重和双精英进化机制来改进樽海鞘群算法,提出了双精英进化樽海鞘群算法(MDSSA),提高算法的搜索能力;其次,运用MDSSA优化ELM的连接权值与阈值,找到ELM的最优参数组合,构建MDSSA-ELM焦炭价格预测模型;最后,在8个基准测试函数上测试MDSSA的收敛性能,在实际焦炭价格数据集上对MDSSA-ELM模型的预测性能进行实验,实验结果表明,MDSSA-ELM相比其他方法预测能力更优,MDSSA相比其他群智能算法搜索能力更强,为焦化企业实现焦炭智慧排产提供了有效的预测工具。
Coke is one of important industrial raw materials,and accurate prediction of its future price trend has great significance for making production scheduling plans of coking plants.Extreme learning machine(ELM)has strong generalization ability and fast computing speed,and it is suitable as the model of coke price prediction.However,the prediction performance of ELM is greatly affected by its key parameters,and its parameters need to be optimized.Based on this,a coke price prediction method is proposed by optimizing the key parameters of ELM using double-elite evolution salp swarm algorithm.Firstly,the double-elite evolutionary salp swarm algorithm(MDSSA)is proposed by introducing logistic chaotic mapping,improved convergence factor,adaptive inertia weights and double-elite evolutionary mechanism,so as to enhance the search capability of salp swarm algorithm(MDSSA).Secondly,the connection weights and thresholds of ELM are optimized using MDSSA for finding the optimal parameters combination,so as to construct the MDSSA-ELM coke price prediction model.Finally,the convergence performance of MDSSA is validated using 8 benchmark functions,and the prediction ability of MDSSA-ELM model is tested on the actual coke price dataset.Experimental results demonstrate that MDSSA-ELM has stronger predictive capability than other methods,and MDSSA has superior searching ability than other algorithms,which provides an effective prediction tool for coking plants for achieving intelligent production scheduling.
作者
朱旭辉
佘孝敏
倪志伟
夏平凡
张琛
ZHU Xuhui;SHE Xiaomin;NI Zhiwei;XIA Pingfan;ZHANG Chen(School of Management,Hefei University of Technology,Hefei 230009,China;Key Laboratory of Process Optimization and Intelligent Decision-making,Ministry of Education,Hefei 230009,China;School of Artificial Intelligence and Big Data,Hefei University,Hefei 230092,China)
出处
《计算机科学》
CSCD
北大核心
2023年第5期292-301,共10页
Computer Science
基金
国家自然科学基金(91546108,71521001)
安徽省自然科学基金(1908085QG298,1908085MG232)
中央高校基本科研业务费专项资金(JZ2019HGTA0053,JZ2019HGBZ0128)
安徽省科技重大专项(201903a05020020)
过程优化与智能决策教育部重点实验室开放课题。
关键词
樽海鞘群算法
极限学习机
双精英进化
焦炭价格预测
Salp swarm algorithm
Extreme learning machine
Double-elite evolution
Coke price prediction
