Markus Wagner 个人学术档案

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引用	4433	3261
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i10 指数	96	83

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Frank NeumannOptimisation and Logistics, School of Computer在 adelaide.edu.au 的电子邮件经过验证
Mehdi NeshatSenior Research Fellow, University of South Australia在 unisa.edu.au 的电子邮件经过验证
Tobias FriedrichChair for Algorithm Engineering, Hasso Plattner Institute, Potsdam, Germany在 hpi.de 的电子邮件经过验证
Christoph TreudeAssociate Professor of Computer Science, Singapore Management University在 smu.edu.sg 的电子邮件经过验证
Nataliia Y. SergiienkoARC Industry Fellow, University of Adelaide在 adelaide.edu.au 的电子邮件经过验证
Carola DoerrCNRS research director (DR) at Sorbonne Université, Paris, France在 mpi-inf.mpg.de 的电子邮件经过验证
Marcella Scoczynski Ribeiro MartinsPhD at Federal University of Technology - Parana UTFPR在 utfpr.edu.br 的电子邮件经过验证
Mohamed El YafraniAalborg University在 mp.aau.dk 的电子邮件经过验证
Mahmoud Bokhari محمود بخاريTaibah University在 taibahu.edu.sa 的电子邮件经过验证
Jakob BossekPaderborn University在 uni-paderborn.de 的电子邮件经过验证
Heike TrautmannProfessor of Machine Learning and Optimisation, Paderborn University, Germany在 uni-paderborn.de 的电子邮件经过验证
Sam NallaperumaUniversity of Cambridge在 cam.ac.uk 的电子邮件经过验证
Ehsan AbbasnejadAustralian Institute for Machine Learning, University of Adelaide在 adelaide.edu.au 的电子邮件经过验证
Davide Astiaso GarciaSapienza University of Rome在 uniroma1.it 的电子邮件经过验证
Sergey Polyakovskiy School of Computer Science, The University of Adelaide在 adelaide.edu.au 的电子邮件经过验证
Alexander E.I. BrownleeSenior Lecturer, University of Stirling, previously Loughborough, Robert Gordon在 cs.stir.ac.uk 的电子邮件经过验证
Ricardo LüdersProfessor Titular, DAINF/CPGEI, Universidade Tecnológica Federal do Paraná在 utfpr.edu.br 的电子邮件经过验证
Myriam DelgadoFederal University of Technology of Paraná在 utfpr.edu.br 的电子邮件经过验证
Aneta NeumannResearcher, The University of Adelaide, Australia在 adelaide.edu.au 的电子邮件经过验证
Lina Bertling TjernbergProfessor in Power Grid Technology在 kth.se 的电子邮件经过验证

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Markus Wagner

Associate Professor of Computer Science, Monash University, Australia

在 monash.edu 的电子邮件经过验证 - 首页

Artificial Intelligence Evolutionary Computation Wave Energy Genetic Improvement Search-Based Software Engineering


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
Evolutionary many-objective optimization: A quick-start guide S Chand, M Wagner Surveys in Operations Research and Management Science 20 (2), 35-42, 2015	174	2015
A deep learning-based evolutionary model for short-term wind speed forecasting: A case study of the Lillgrund offshore wind farm M Neshat, MM Nezhad, E Abbasnejad, S Mirjalili, LB Tjernberg, ... Energy conversion and management 236, 114002, 2021	159	2021
A comprehensive benchmark set and heuristics for the traveling thief problem S Polyakovskiy, MR Bonyadi, M Wagner, Z Michalewicz, F Neumann Proceedings of the 2014 annual conference on genetic and evolutionary …, 2014	130	2014
Benchmarking in optimization: Best practice and open issues T Bartz-Beielstein, C Doerr, D Berg, J Bossek, S Chandrasekaran, ... arXiv preprint arXiv:2007.03488, 2020	126	2020
A Fast and Effective Local Search Algorithm for Optimizing the Placement of Wind Turbines M Wagner, J Day, F Neumann Renewable Energy 51, 64-70, 2013	126	2013
Development of underground mine monitoring and communication system integrated ZigBee and GIS MA Moridi, Y Kawamura, M Sharifzadeh, EK Chanda, M Wagner, H Jang, ... International Journal of Mining Science and Technology 25 (5), 811-818, 2015	119	2015
Predicting the energy output of wind farms based on weather data: Important variables and their correlation E Vladislavleva, T Friedrich, F Neumann, M Wagner Renewable Energy 50, 236-243, 2013	103	2013
Approximation-guided evolutionary multi-objective optimization K Bringmann, T Friedrich, F Neumann, M Wagner IJCAI Proceedings-International Joint Conference on Artificial Intelligence …, 2011	103	2011
On the use of genetic programming to evolve priority rules for resource constrained project scheduling problems S Chand, Q Huynh, H Singh, T Ray, M Wagner Information Sciences 432, 146-163, 2018	98	2018
A novel feature-based approach to characterize algorithm performance for the traveling salesperson problem O Mersmann, B Bischl, H Trautmann, M Wagner, J Bossek, F Neumann Annals of Mathematics and Artificial Intelligence 69, 151-182, 2013	98	2013
A fast approximation-guided evolutionary multi-objective algorithm M Wagner, F Neumann Proceedings of the 15th annual conference on Genetic and evolutionary …, 2013	86	2013
Performance analysis of ZigBee network topologies for underground space monitoring and communication systems MA Moridi, Y Kawamura, M Sharifzadeh, EK Chanda, M Wagner, ... Tunnelling and Underground Space Technology 71, 201-209, 2018	84	2018
A case study of algorithm selection for the traveling thief problem M Wagner, M Lindauer, M Mısır, S Nallaperuma, F Hutter Journal of Heuristics 24, 295-320, 2018	82	2018
Wind turbine power output prediction using a new hybrid neuro-evolutionary method M Neshat, MM Nezhad, E Abbasnejad, S Mirjalili, D Groppi, A Heydari, ... Energy 229, 120617, 2021	80	2021
Rosita: Towards automatic elimination of power-analysis leakage in ciphers MA Shelton, N Samwel, L Batina, F Regazzoni, M Wagner, Y Yarom arXiv preprint arXiv:1912.05183, 2019	71	2019
Approximate approaches to the traveling thief problem H Faulkner, S Polyakovskiy, T Schultz, M Wagner Proceedings of the 2015 annual conference on genetic and evolutionary …, 2015	70	2015
Faster black-box algorithms through higher arity operators B Doerr, D Johannsen, T Kötzing, PK Lehre, M Wagner, C Winzen Proceedings of the 11th workshop proceedings on Foundations of genetic …, 2011	68	2011
Metaheuristics “in the large” J Swan, S Adriaensen, AEI Brownlee, K Hammond, CG Johnson, A Kheiri, ... European Journal of Operational Research 297 (2), 393-406, 2022	66	2022
Optimizing the layout of 1000 wind turbines M Wagner, K Veeramachaneni, F Neumann, UM O’Reilly European wind energy association annual event 205209, 2011	66	2011
A hybrid cooperative co-evolution algorithm framework for optimising power take off and placements of wave energy converters M Neshat, B Alexander, M Wagner Information Sciences 534, 218-244, 2020	64	2020

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