Supercapacitors can be used for portable energy storage applications. In this study, machine learning techniques are applied to optimize the process of preparation of supercapacitor electrodes from chemically activated carbon made from jackfruit seeds. Experimental trials were carried out using statistical design of experiments. Artificial neural network was employed to generate the process model and a multiobjective optimization was attempted by means of swarm intelligence and the Derringer's desirability function. The optimized electrode demonstrated high capacitance and low resistance making it suitable for supercapacitors. The algorithm developed in the study can be adopted by process engineers for efficient optimization.

中文翻译：

---

基于机器学习的菠萝蜜种子基超级电容器电极的建模和优化

超级电容器可用于便携式储能应用。在这项研究中，机器学习技术被应用于优化由菠萝蜜种子制成的化学活性炭制备超级电容器电极的过程。使用实验的统计设计进行实验。运用人工神经网络生成过程模型，并通过群体智能和Derringer的合意函数尝试进行多目标优化。经过优化的电极表现出高电容和低电阻，使其适用于超级电容器。研究工程师开发的算法可以为过程工程师所采用，以进行有效的优化。