.png){kind=icon}
返回
Modeling a PEMFC by a support vector machine
.png){kind=icon}
PRE
AI
DOI：10.1016/j.jpowsour.2006.01.040.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This paper reports a modeling study of proton exchange membrane fuel cell (PEMFC) performance by using a support vector machine (SVM). A PEMFC is a nonlinear, multi-variable system that is hard to model by conventional methods. As regards the SVM, it has a superior capability for generalization, and this capability is independent on the dimensionality of the input data. These two merits combine to make it a powerful tool to predict how a PEMFC will behave under different operating conditions. Herein a SVM model of a PEMFC system is built, optimized and tested. First, the model is determined with selected experimental data, and then it is used to predict PEMFC performance. It is shown that the model can make the prediction in 10 ms with the squared correlation coefficient as high as 99.7%. Therefore, the proposed black-box SVM PEMFC model applies to the simulation, real-time control and monitoring of a fuel cell's performance. (c) 2006 Elsevier B.V. All rights reserved.
Keyword:
fuel cell modeling
proton exchange membrane fuel cell (PEMFC)
support vector machine (SVM)
support vector regression (SVR)
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
7.9
论文数:
3.7W
被引数:
15.0W
机构
暂无机构信息
引用论文
On the Development and Applications of Cellulosic Nanofibrillar and Nanocrystalline Materials纤维素纳米原纤和纳米晶材料的发展与应用
PREAI
分享收藏Acquired Resistance of Lung Adenocarcinomas to Gefitinib or Erlotinib Is Associated with a Second Mutation in the EGFR Kinase Domain肺腺癌对吉非替尼或厄洛替尼的获得性耐药与EGFR激酶结构域的第二个突变有关
OAAI
OAAI分享收藏分享收藏Practical selection of SVM parameters and noise estimation for SVM regressionSVM回归中SVM参数的实用选择和噪声估计.png)
NEURAL NETWORKSOAAI
NEURAL NETWORKSIF6.3
OAAI分享收藏On-board fuel cell power supply modeling on the basis of neural network methodology基于神经网络方法的车载燃料电池电源建模
PREAI
分享收藏Physical and Electrical Characteristics of Physical Vapor-Deposited Tungsten for Bit Line Process
PREAI
分享收藏
查看更多内容