System identification of PEM fuel cells using an improved Elman neural network and a new hybrid optimization algorithm
Dongmin Yu,Dongmin Yu,Yong Wang,Yong Wang,Huanan Liu,Huanan Liu,Kittisak Jermsittiparsert,Navid Razmjooy +7 more
TLDR
An optimized improved Elman neural network based on a new hybrid optimization algorithm is proposed for increasing their efficiency in the next designs of the proton exchange membrane fuel cell.About:
This article is published in Energy Reports.The article was published on 2019-11-01 and is currently open access. It has received 132 citations till now. The article focuses on the topics: Hybrid algorithm & System identification.read more
Citations
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Journal ArticleDOI
A novel PEMFC-CHP system for methanol reforming as fuel purified by hydrogen permeation alloy membrane
TL;DR: Based on Aspen Plus, a novel fuel electrochemical power generation system is proposed which integrates the chemical fuel conversion process and the proton exchange membrane fuel cell (PEMFC) unit as mentioned in this paper .
The increasing market of ecommerce and its impact on retailer
TL;DR: In this paper, the impact and development of e-commerce and its effect on national and worldwide market is examined and the authors explore how E-commerce as a part of their routine life and acquired a change the inclinations of the shopper along these lines contacting every one of their lives.
Journal ArticleDOI
A Novel Pemfc-Chp System for Methanol Reforming as Fuel Purified by Hydrogen Permeation Alloy Membrane
Journal ArticleDOI
Offline and online parameter estimation of nonlinear systems: Application to a solid oxide fuel cell system.
TL;DR: In this article , an offline tuning strategy and an online parameter estimation method are exploited to calibrate the solid oxide fuel cell mathematical model, which is designed in order to tune the model under various operation conditions.
Book ChapterDOI
An Initial Approach About Data Preprocessing Techniques Applied to Polymer Electrolyte Fuel Cells: A Case Study
TL;DR: In this paper, the authors provide the pathway to follow when a fuel cell's collected dataset is used to solve a supervised learning problem such as classification and regression, which impacts on better learning, generalization, prediction, and computational time.
References
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Polymer Electrolyte Fuel Cell Model
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