详细信息
Research on Activated Carbon Supercapacitors Electrochemical Properties Based on Improved PSO-BP Neural Network ( SCI-EXPANDED收录)
文献类型:期刊文献
英文题名:Research on Activated Carbon Supercapacitors Electrochemical Properties Based on Improved PSO-BP Neural Network
作者:Liang, Xiaoyi[1,2];Yang, Zhen[1,2];Gu, Xingsheng[3];Ling, Licheng[1,2]
机构:[1]E China Univ Sci & Technol, State Key Lab Chem Engn, Shanghai 200237, Peoples R China;[2]Minist Educ, Key Lab Special Funct Polymer Mat & Their Related, Shanghai 200237, Peoples R China;[3]E China Univ Sci & Technol, Inst Informat Sci, Shanghai 200237, Peoples R China
年份:2009
卷号:13
期号:2
起止页码:135
外文期刊名:CMC-COMPUTERS MATERIALS & CONTINUA
收录:;WOS:【SCI-EXPANDED(收录号:WOS:000277068000003)】;
基金:This work was partly supported by National Science Foundation of China (No. 50730003 and No. 50672025), National Project of Scientific and Technical Supporting Programs Funded by Ministry of Science & Technology of China (No. 2007BAE55B00), National High Technology Research and Development Program of China (No. 2007AA05Z311), and Program for New Century Excellent Talents in University (NCET-07-0285).
语种:英文
外文关键词:Activated Carbon EDLC; Electrochemical Property; Neural Network; Particle Swarm Optimization
摘要:Supercapacitors, also called electrical double-layer capacitors (EDLCs), occupy a region between batteries and dielectric capacitors on the Ragone plot describing the relation between energy and power. BET specific surface area and specific capacitance are two important electrochemical property parameters for activated carbon EDLCs, which are usually tested by experimental method. However, it is misspent time to repeat lots of experiments for EDLCs' studies. In this investigation, we developed one theoretical model based on improved particle swarm optimization algorithm back propagation (PSO-BP) neural network (NN) to simulate and optimize BET specific surface area and specific capacitance. Comparative studies between the predicted data and experimental data-earlier deduced by Liu et al, have revealed that improved PSO-BPNN model bears higher prediction accuracy, faster computation speed and better generalization performance. It is concluded that the improved PSO-BP NN is one simple and effective method to find optimal conditions of BET specific surface area and specific capacitance for activated carbon EDLCs.
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