A comprehensive review on parameter estimation techniques for Proton Exchange Membrane fuel cell modelling
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[1] Ali Keyhani,et al. Neural Network Modeling of Proton Exchange Membrane Fuel Cell , 2010, IEEE Transactions on Energy Conversion.
[2] Ning Wang,et al. A novel P systems based optimization algorithm for parameter estimation of proton exchange membrane fuel cell model , 2012 .
[3] J Timmis,et al. An artificial immune system for data analysis. , 2000, Bio Systems.
[4] Alireza Rezazadeh,et al. Artificial immune system-based parameter extraction of proton exchange membrane fuel cell , 2011 .
[5] Kan Wu,et al. A multiple colonies artificial bee colony algorithm for a capacitated vehicle routing problem and re-routing strategies under time-dependent traffic congestion , 2017, Comput. Ind. Eng..
[6] K. Agbossou,et al. Characterization of a Ballard MK5-E Proton Exchange Membrane Fuel Cell Stack , 2001 .
[7] Y. Wang,et al. Modeling and Dynamic Characteristic Simulation of a Proton Exchange Membrane Fuel Cell , 2009, IEEE Transactions on Energy Conversion.
[8] Alireza Askarzadeh,et al. Bird mating optimizer: An optimization algorithm inspired by bird mating strategies , 2014, Commun. Nonlinear Sci. Numer. Simul..
[9] N. Rajasekar,et al. A comprehensive review on solar PV maximum power point tracking techniques , 2017 .
[10] Kazuyuki Mori,et al. Immune Algorithm with Searching Diversity and its Application to Resource Allocation Problem , 1993 .
[11] Chaohua Dai,et al. Seeker Optimization Algorithm for Digital IIR Filter Design , 2010, IEEE Transactions on Industrial Electronics.
[12] Dervis Karaboga,et al. A modified Artificial Bee Colony algorithm for real-parameter optimization , 2012, Inf. Sci..
[13] Ning Wang,et al. Circular genetic operators based RNA genetic algorithm for modeling proton exchange membrane fuel cells , 2014 .
[14] Byung Soo Kim,et al. A hybrid genetic algorithm with two-stage dispatching heuristic for a machine scheduling problem with step-deteriorating jobs and rate-modifying activities , 2016, Comput. Ind. Eng..
[15] Zbigniew Michalewicz,et al. Genetic Algorithms + Data Structures = Evolution Programs , 1996, Springer Berlin Heidelberg.
[16] Alireza Rezazadeh,et al. Extraction of maximum power point in solar cells using bird mating optimizer-based parameters identification approach , 2013 .
[17] Didier Mayer,et al. A new approach to empirical electrical modelling of a fuel cell, an electrolyser or a regenerative fuel cell , 2004 .
[18] N. Rajasekar,et al. Comparative study of PEM fuel cell parameter extraction using Genetic Algorithm , 2015 .
[19] Ning Wang,et al. Parameter identification of PEMFC model based on hybrid adaptive differential evolution algorithm , 2015 .
[20] P Gheorghe,et al. Tracing Some Open Problems in Membrane Computing , 2007 .
[21] R. Venkata Rao,et al. Teaching-Learning-Based Optimization: An optimization method for continuous non-linear large scale problems , 2012, Inf. Sci..
[22] Xianguo Li,et al. Mathematical modeling of proton exchange membrane fuel cells , 2001 .
[23] C. D. Gelatt,et al. Optimization by Simulated Annealing , 1983, Science.
[24] M. Sedighizadeh,et al. A Tribe Particle Swarm Optimization for Parameter Identification of Proton Exchange Membrane Fuel Cell (TECHNICAL NOTE) , 2014 .
[25] Koan-Yuh Chang,et al. The optimal design for PEMFC modeling based on Taguchi method and genetic algorithm neural networks , 2011 .
[26] Uday K. Chakraborty,et al. PEM fuel cell modeling using differential evolution , 2012 .
[27] Daniel Hissel,et al. Characterisation and modelling of a 5 kW PEMFC for transportation applications , 2006 .
[28] David E. Goldberg,et al. Genetic algorithms and Machine Learning , 1988, Machine Learning.
[29] Yonghua Song,et al. Seeker optimization algorithm: A novel stochastic search algorithm for global numerical optimization , 2010 .
[30] M. Sedighizadeh,et al. Parameter Optimization for a Pemfc Model With Particle Swarm Optimization , 2011 .
[31] Andrew Lewis,et al. Grey Wolf Optimizer , 2014, Adv. Eng. Softw..
[32] M.G. Simoes,et al. Sensitivity analysis of the modeling parameters used in Simulation of proton exchange membrane fuel cells , 2005, IEEE Transactions on Energy Conversion.
[33] Cédric Damour,et al. Mechanistic Model versus Artificial Neural Network Model of a Single-Cell PEMFC , 2014 .
[34] R. O’Hayre,et al. Fuel Cell Fundamentals , 2005 .
[35] Leandro dos Santos Coelho,et al. A backtracking search algorithm combined with Burger's chaotic map for parameter estimation of PEMFC electrochemical model , 2014 .
[36] X. D. Xue,et al. Unified mathematical modelling of steady-state and dynamic voltage–current characteristics for PEM fuel cells , 2006 .
[37] Wenyin Gong,et al. Parameter optimization of PEMFC model with improved multi-strategy adaptive differential evolution , 2014, Eng. Appl. Artif. Intell..
[38] Xin-Jian Zhu,et al. Parameter optimization for a PEMFC model with a hybrid genetic algorithm , 2006 .
[39] R. Venkata Rao,et al. Teaching-learning-based optimization: A novel method for constrained mechanical design optimization problems , 2011, Comput. Aided Des..
[40] Riccardo Poli,et al. Particle swarm optimization , 1995, Swarm Intelligence.
[41] N. Rajasekar,et al. A novel approach for fuel cell parameter estimation using simple Genetic Algorithm , 2015 .
[42] Mei-Ling Huang,et al. Modified artificial bee colony algorithm for scheduling optimization for printed circuit board production , 2017 .
[43] Pierre R. Roberge,et al. Development and application of a generalised steady-state electrochemical model for a PEM fuel cell , 2000 .
[44] Zong Woo Geem,et al. A New Heuristic Optimization Algorithm: Harmony Search , 2001, Simul..
[45] Chaohua Dai,et al. Seeker Optimization Algorithm for Optimal Reactive Power Dispatch , 2009, IEEE Transactions on Power Systems.
[46] A. T. de Almeida,et al. A new parameter extraction method for accurate modeling of PEM fuel cells , 2009 .
[47] N. Rajasekar,et al. Design and overview of maximum power point tracking techniques in wind and solar photovoltaic systems: A review , 2017 .
[48] Alireza Rezazadeh,et al. A grouping-based global harmony search algorithm for modeling of proton exchange membrane fuel cell , 2011 .
[49] H. Toghiani,et al. Steady state and dynamic performance of proton exchange membrane fuel cells (PEMFCs) under various operating conditions and load changes , 2006 .
[50] Rainer Storn,et al. Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..
[51] N. Rajasekar,et al. Critical Evaluation of Genetic Algorithm Based Fuel Cell Parameter Extraction , 2015 .
[52] Chaohua Dai,et al. Seeker Optimization Algorithm , 2006, 2006 International Conference on Computational Intelligence and Security.
[53] Kathryn A. Dowsland,et al. Simulated Annealing , 1989, Encyclopedia of GIS.
[54] Kauko Leiviskä,et al. Validation of genetic algorithm results in a fuel cell model , 2010 .
[55] Hassan Noura,et al. The parameter identification of the Nexa 1.2 kW PEMFC's model using particle swarm optimization , 2015 .
[56] Dan Simon,et al. Biogeography-Based Optimization , 2022 .
[57] Alireza Rezazadeh,et al. Optimization of PEMFC model parameters with a modified particle swarm optimization , 2011 .
[58] Alireza Rezazadeh,et al. An Innovative Global Harmony Search Algorithm for Parameter Identification of a PEM Fuel Cell Model , 2012, IEEE Transactions on Industrial Electronics.
[59] Luciane Neves Canha,et al. An electrochemical-based fuel-cell model suitable for electrical engineering automation approach , 2004, IEEE Transactions on Industrial Electronics.
[60] N. Jenkins,et al. Proton exchange membrane (PEM) fuel cell stack configuration using genetic algorithms , 2004 .
[61] Oguz Emrah Turgut,et al. Optimal proton exchange membrane fuel cell modelling based on hybrid Teaching Learning Based Optimization – Differential Evolution algorithm , 2016 .
[62] Wen-Yeau Chang. Equivalent Circuit Parameters Estimation for PEM Fuel Cell Using RBF Neural Network and Enhanced Particle Swarm Optimization , 2013 .
[63] D. Karaboga,et al. A Simple and Global Optimization Algorithm for Engineering Problems: Differential Evolution Algorithm , 2004 .
[64] Pinar Çivicioglu,et al. Backtracking Search Optimization Algorithm for numerical optimization problems , 2013, Appl. Math. Comput..
[65] Gheorghe Paun,et al. Membrane Computing , 2002, Natural Computing Series.
[66] Alireza Rezazadeh,et al. A new heuristic optimization algorithm for modeling of proton exchange membrane fuel cell: bird mating optimizer , 2013 .
[67] Yulong Xu,et al. A Hybrid Differential Evolution for Optimum Modeling of PEM Fuel Cells , 2014 .
[68] N. Rajasekar,et al. Metaheuristic algorithms for PV parameter identification: A comprehensive review with an application to threshold setting for fault detection in PV systems , 2018 .
[69] Alireza Rezazadeh,et al. A new artificial bee swarm algorithm for optimization of proton exchange membrane fuel cell model parameters , 2011, Journal of Zhejiang University SCIENCE C.
[70] Soteris A. Kalogirou,et al. Artificial intelligence techniques for photovoltaic applications: A review , 2008 .
[71] Ned Djilali,et al. Computational modelling of polymer electrolyte membrane (PEM) fuel cells: Challenges and opportunities , 2007 .
[72] Kang Li,et al. An improved TLBO with elite strategy for parameters identification of PEM fuel cell and solar cell models , 2014 .
[73] Weifeng Gao,et al. A modified artificial bee colony algorithm , 2012, Comput. Oper. Res..
[74] Cuimei Bo,et al. Modeling and optimization for proton exchange membrane fuel cell stack using aging and challenging P systems based optimization algorithm , 2016 .
[75] Xuesong Yan,et al. Parameter extraction of different fuel cell models with transferred adaptive differential evolution , 2015 .
[76] Eberhard Gill,et al. Swarm satellite mission scheduling & planning using Hybrid Dynamic Mutation Genetic Algorithm , 2017 .
[77] Willy Charon,et al. Real time modelling of the dynamic mechanical behaviour of PEMFC thanks to neural networks , 2013, Eng. Appl. Artif. Intell..
[78] Gexiang Zhang,et al. Parameter fitting of PEMFC models based on adaptive differential evolution , 2014 .
[79] N. Rajasekar,et al. Analysis on solar PV emulators: A review , 2018 .
[80] Chaohua Dai,et al. Reactive power dispatch considering voltage stability with seeker optimization algorithm , 2009 .
[81] Atilla Biyikoglu,et al. Review of proton exchange membrane fuel cell models , 2005 .
[82] M. Fesanghary,et al. An improved harmony search algorithm for solving optimization problems , 2007, Appl. Math. Comput..
[83] Q. Niu,et al. A biogeography-based optimization algorithm with mutation strategies for model parameter estimation of solar and fuel cells , 2014 .
[84] Meiying Ye,et al. Parameter identification for proton exchange membrane fuel cell model using particle swarm optimization , 2009 .
[85] Qi Li,et al. Parameter Identification for PEM Fuel-Cell Mechanism Model Based on Effective Informed Adaptive Particle Swarm Optimization , 2011, IEEE Transactions on Industrial Electronics.
[86] Gheorghe Paun,et al. Computing with Membranes , 2000, J. Comput. Syst. Sci..
[87] N. Rajasekar,et al. Genetic Algorithm-based Modeling of PEM Fuel Cells Suitable for Integration in DC Microgrids , 2017 .
[88] Wenyin Gong,et al. Accelerating parameter identification of proton exchange membrane fuel cell model with ranking-based differential evolution , 2013 .