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Bradley Alexander
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Publications
- 2023
- [d2]Mehdi Neshat, Bradley Alexander, Nataliia Y. Sergiienko, Markus Wagner:
Large-scale Wave Energy Farm. UCI Machine Learning Repository, 2023 - 2021
- [c16]Sæmundur Óskar Haraldsson, Alexander E. I. Brownlee, John R. Woodward, Markus Wagner
, Bradley Alexander:
Genetic improvement: taking real-world source code and improving it using genetic programming. GECCO Companion 2021: 786-817 - 2020
- [j4]Mehdi Neshat
A hybrid cooperative co-evolution algorithm framework for optimising power take off and placements of wave energy converters. Inf. Sci. 534: 218-244 (2020) - [j3]Mehdi Neshat
New insights into position optimisation of wave energy converters using hybrid local search. Swarm Evol. Comput. 59: 100744 (2020) - [c15]Mehdi Neshat
Optimisation of large wave farms using a multi-strategy evolutionary framework. GECCO 2020: 1150-1158 - [i15]Nataliia Y. Sergiienko
Design optimisation of a multi-mode wave energy converter. CoRR abs/2001.08966 (2020) - [i14]Mehdi Neshat, Meysam Majidi Nezhad, Ehsan Abbasnejad, Lina Bertling Tjernberg, Davide Astiaso Garcia, Bradley Alexander, Markus Wagner:
An Evolutionary Deep Learning Method for Short-term Wind Speed Prediction: A Case Study of the Lillgrund Offshore Wind Farm. CoRR abs/2002.09106 (2020) - [i12]Mehdi Neshat, Bradley Alexander, Nataliia Y. Sergiienko, Markus Wagner:
Optimisation of Large Wave Farms using a Multi-strategy Evolutionary Framework. CoRR abs/2003.09594 (2020) - [i11]Mehdi Neshat, Meysam Majidi Nezhad, Ehsan Abbasnejad, Daniele Groppi, Azim Heydari, Lina Bertling Tjernberg, Davide Astiaso Garcia, Bradley Alexander, Markus Wagner:
Hybrid Neuro-Evolutionary Method for Predicting Wind Turbine Power Output. CoRR abs/2004.12794 (2020) - 2019
- [c14]Mahmoud A. Bokhari
Mind the gap - a distributed framework for enabling energy optimisation on modern smart-phones in the presence of noise, drift, and statistical insignificance. CEC 2019: 1330-1337 - [c13]Mehdi Neshat
A hybrid evolutionary algorithm framework for optimising power take off and placements of wave energy converters. GECCO 2019: 1293-1301 - [c12]Mehdi Neshat
Adaptive Neuro-Surrogate-Based Optimisation Method for Wave Energy Converters Placement Optimisation. ICONIP (2) 2019: 353-366 - [d1]Mehdi Neshat, Markus Wagner, Bradley Alexander:
Wave Energy Converters. UCI Machine Learning Repository, 2019 - [i10]Mehdi Neshat, Bradley Alexander, Nataliia Y. Sergiienko, Markus Wagner:
A Hybrid Evolutionary Algorithm Framework for Optimising Power Take Off and Placements of Wave Energy Converters. CoRR abs/1904.07043 (2019) - [i9]Mehdi Neshat, Bradley Alexander, Nataliia Y. Sergiienko, Markus Wagner:
A new insight into the Position Optimization of Wave Energy Converters by a Hybrid Local Search. CoRR abs/1904.09599 (2019) - [i8]Mehdi Neshat, Ehsan Abbasnejad, Qinfeng Shi, Bradley Alexander, Markus Wagner:
Adaptive Neuro-Surrogate-Based Optimisation Method for Wave Energy Converters Placement Optimisation. CoRR abs/1907.03076 (2019) - [i6]Mehdi Neshat, Bradley Alexander, Markus Wagner:
A Hybrid Cooperative Co-evolution Algorithm Framework for Optimising Power Take Off and Placements of Wave Energy Converters. CoRR abs/1910.01280 (2019) - 2018
- [c9]Mehdi Neshat
A detailed comparison of meta-heuristic methods for optimising wave energy converter placements. GECCO 2018: 1318-1325 - [c7]Mahmoud A. Bokhari
In-vivo and offline optimisation of energy use in the presence of small energy signals: A case study on a popular Android library. MobiQuitous 2018: 207-215 - 2017
- [c4]Mahmoud A. Bokhari
Deep parameter optimisation on Android smartphones for energy minimisation: a tale of woe and a proof-of-concept. GECCO (Companion) 2017: 1501-1508 - [i3]Mahmoud A. Bokhari, Yuanzhong Xia, Bo Zhou, Bradley Alexander, Markus Wagner:
Validation of Internal Meters of Mobile Android Devices. CoRR abs/1701.07095 (2017)
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