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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Optimal operational strategy of hybrid PV/wind renewable energy system using homer: a case study
TL;DR: In this article, the authors presented an optimal configuration of a hybrid renewable energy source with a wind turbine and a photovoltaic system to fulfil the required electricity power of a medium-size workshop.
Journal ArticleDOI
A new optimal energy management strategy based on improved multi-objective antlion optimization algorithm: applications in smart home
TL;DR: This paper presents an optimal schedule for the consumption of residential appliances based on improved multi-objective antlion optimization algorithm to minimize the electrical cost and the user comfort and shows the superiority of the proposed algorithm.
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Multi-objective optimization for efficient modeling and improvement of the high temperature PEM fuel cell based Micro-CHP system
TL;DR: This study presents a multi-objective optimization method to provide an optimal design parameters for the HT-PEMFC based micro-CHP during a 14,000 h lifetime by considering the effect of degradation to optimize the net electrical efficiency and the electrical power generation.
Journal ArticleDOI
Predicting of Runoff Using an Optimized SWAT-ANN: A Case Study
TL;DR: In this paper, the authors used the SWAT and ANN models and an improved model of a metaheuristic employed for resolving the explained shortcoming, which is based on a Mutated model of the Whale Optimization Algorithm (MWOA) that enhances the expected results by reducing the error in the ANN.
Journal ArticleDOI
Parameter identification of proton exchange membrane fuel cell via Levenberg-Marquardt backpropagation algorithm
Bo Yang,Chunyuan Zeng,Long Wang,Yinyuan Guo,Guanghua Chen,Zhengxun Guo,Yijun Chen,Danyang Li,Pulin Cao,Hongchun Shu,Tao Yu,Jiawei Zhu +11 more
TL;DR: Levenberg-Marquardt backpropagation (LMBP) algorithm based on artificial neural networks (ANNs) is proposed for PEMFC parameter identification and simulation results indicate that LMBP performs a higher accuracy and faster speed for parameter identification.
References
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The Whale Optimization Algorithm
Seyedali Mirjalili,Andrew Lewis +1 more
TL;DR: Optimization results prove that the WOA algorithm is very competitive compared to the state-of-art meta-heuristic algorithms as well as conventional methods.
Journal ArticleDOI
A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm
Dervis Karaboga,Bahriye Basturk +1 more
TL;DR: Artificial Bee Colony (ABC) Algorithm is an optimization algorithm based on the intelligent behaviour of honey bee swarm that is used for optimizing multivariable functions and the results showed that ABC outperforms the other algorithms.
Proceedings ArticleDOI
On genetic algorithms
TL;DR: C Culling is near optimal for this problem, highly noise tolerant, and the best known a~~roach in some regimes, and some new large deviation bounds on this submartingale enable us to determine the running time of the algorithm.
Journal ArticleDOI
Polymer Electrolyte Fuel Cell Model
TL;DR: In this paper, an isothermal, one-dimensional, steady-state model for a complete polymer electrolyte fuel cell (PEFC) with a 117 Nation | membrane is presented, which predicts an increase in membrane resistance with increased current density and demonstrates the great advantage of a thinner membrane in alleviating this resistance problem.