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A Hybrid Multi-gene Genetic Programming with Capuchin Search Algorithm for Modeling a Nonlinear Challenge Problem: Modeling Industrial Winding Process, Case Study
Neural Processing Letters ( IF 3.1 ) Pub Date : 2021-05-20 , DOI: 10.1007/s11063-021-10530-w
Malik Braik

Motivated by the increasing complexity and operational productivity of industrial processes, the need for efficient modeling schemes for industrial systems is highly demanded. This study presents a new simulator model for a real winding process based on a combination of Multi-gene Genetic Programming (MGP) and Capuchin Search Algorithm (CapSA), referred to as MGP-CapSA modeling approach. CapSA is a meta-heuristic algorithm used to optimize the coefficients of the regression equations of the MGP technique. The winding process has tensions in the web between reels 1 and 2 and between reels 2 and 3. On this basis, two mathematical models were developed by the MGP-CapSA method to estimate the tensions in the web for this process. The efficacy and superiority of the proposed MGP-CapSA method were verified by extensive experiments and hypothesis testing, and the proposed method was then compared with other well-known intelligent and conventional modeling methods. The proposed MGP-CapSA method can be exploited to enhance control performance and achieve robust fault-tolerant system. A comparison of the MGP-CapSA method with other promising modeling methods corroborates the performance level of MGP-CapSA over those competitors. The results demonstrate that MGP-CapSA is a suitable method for generating robust models for complex nonlinear systems.



中文翻译:

带有非线性查询问题的Capuchin搜索算法的混合多基因遗传规划:工业绕组过程建模,案例研究

由于工业过程的复杂性和操作生产率的提高,迫切需要工业系统的有效建模方案。这项研究基于多基因遗传编程(MGP)和卷尾猴搜索算法(CapSA)的组合,提出了一种用于实际绕组过程的新模拟器模型,称为MGP-CapSA建模方法。CapSA是一种元启发式算法,用于优化MGP技术的回归方程的系数。卷绕过程中,卷轴1和2之间以及卷轴2和3之间的卷材中都有张力。在此基础上,通过MGP-CapSA方法开发了两个数学模型,以估算此过程中卷材中的张力。通过广泛的实验和假设检验,验证了所提出的MGP-CapSA方法的有效性和优越性,然后将所提出的方法与其他知名的智能和常规建模方法进行比较。可以利用所提出的MGP-CapSA方法来增强控制性能并实现鲁棒的容错系统。MGP-CapSA方法与其他有希望的建模方法的比较证实了MGP-CapSA在这些竞争对手之上的性能水平。结果表明,MGP-CapSA是生成复杂非线性系统鲁棒模型的合适方法。MGP-CapSA方法与其他有前途的建模方法的比较证实了MGP-CapSA在这些竞争对手之上的性能水平。结果表明,MGP-CapSA是生成复杂非线性系统鲁棒模型的合适方法。MGP-CapSA方法与其他有希望的建模方法的比较证实了MGP-CapSA在这些竞争对手之上的性能水平。结果表明,MGP-CapSA是生成复杂非线性系统鲁棒模型的合适方法。

更新日期:2021-05-22
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