H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Engineering and Technology D-index 54 Citations 10,470 123 World Ranking 1104 National Ranking 486

Overview

What is he best known for?

The fields of study he is best known for:

  • Statistics
  • Artificial intelligence
  • Machine learning

Patrick M. Reed focuses on Mathematical optimization, Multi-objective optimization, Evolutionary algorithm, Water resources and Genetic algorithm. His Mathematical optimization research focuses on subjects like Sampling, which are linked to Kriging. His Multi-objective optimization research incorporates elements of Visualization, Decision support system and Artificial intelligence.

His studies in Evolutionary algorithm integrate themes in fields like Evolutionary computation, Hydrological modelling, Management science and Benchmark. His Water resources research integrates issues from Environmental resource management and Water supply. His Water supply research is multidisciplinary, incorporating elements of Robust decision-making and Operations research.

His most cited work include:

  • State of the Art for Genetic Algorithms and Beyond in Water Resources Planning and Management (418 citations)
  • Borg: An auto-adaptive many-objective evolutionary computing framework (411 citations)
  • Evolutionary algorithms and other metaheuristics in water resources (337 citations)

What are the main themes of his work throughout his whole career to date?

His primary areas of investigation include Mathematical optimization, Evolutionary algorithm, Multi-objective optimization, Water supply and Environmental resource management. Patrick M. Reed has included themes like Sampling and Sobol sequence, Sensitivity in his Mathematical optimization study. The concepts of his Evolutionary algorithm study are interwoven with issues in Management science and Benchmark.

His research on Management science frequently connects to adjacent areas such as Risk analysis. His work in Multi-objective optimization tackles topics such as Genetic algorithm which are related to areas like Sorting. His research investigates the link between Water supply and topics such as Water resources that cross with problems in Operations research.

He most often published in these fields:

  • Mathematical optimization (20.16%)
  • Evolutionary algorithm (18.55%)
  • Multi-objective optimization (15.32%)

What were the highlights of his more recent work (between 2018-2021)?

  • Water supply (11.69%)
  • Environmental resource management (10.89%)
  • Drainage basin (4.03%)

In recent papers he was focusing on the following fields of study:

Patrick M. Reed mainly focuses on Water supply, Environmental resource management, Drainage basin, Water resource management and Mathematical optimization. His study explores the link between Water supply and topics such as Environmental economics that cross with problems in Investment, Streamflow and Water infrastructure. Patrick M. Reed usually deals with Drainage basin and limits it to topics linked to Flood myth and Parametric statistics, Water balance and Multi reservoir.

His work deals with themes such as Water scarcity, Groundwater, Interoperability, Adaptive management and Hydrology, which intersect with Water resource management. As part of the same scientific family, Patrick M. Reed usually focuses on Hydrology, concentrating on Financial risk and intersecting with Natural resource economics, Evolutionary algorithm and Portfolio. His Multi-objective optimization and Reservoir operation study in the realm of Mathematical optimization connects with subjects such as Space.

Between 2018 and 2021, his most popular works were:

  • Balancing Hydropower Development and Ecological Impacts in the Mekong: Tradeoffs for Sambor Mega Dam (24 citations)
  • Deep Uncertainties in Sea-Level Rise and Storm Surge Projections: Implications for Coastal Flood Risk Management. (23 citations)
  • Robust abatement pathways to tolerable climate futures require immediate global action (22 citations)

In his most recent research, the most cited papers focused on:

  • Statistics
  • Artificial intelligence
  • Machine learning

Patrick M. Reed mostly deals with Water supply, Environmental resource management, Robustness, Multi-objective optimization and Mathematical optimization. The Water supply study combines topics in areas such as Environmental economics and Decision rule. His Environmental resource management research incorporates themes from Water scarcity, Drainage basin, Land cover, Complex system and Robustness.

His studies deal with areas such as Risk analysis, Joint and Reservoir operation as well as Robustness. The various areas that Patrick M. Reed examines in his Multi-objective optimization study include Control, Stochastic control and Control theory, Sensitivity. His research in Mathematical optimization intersects with topics in Reduction methods and Representation.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

State of the Art for Genetic Algorithms and Beyond in Water Resources Planning and Management

John Nicklow;Patrick Reed;Dragan Savic;Tibebe Dessalegne.
Journal of Water Resources Planning and Management (2010)

598 Citations

Borg: An auto-adaptive many-objective evolutionary computing framework

David Hadka;Patrick Reed.
Evolutionary Computation (2013)

553 Citations

Evolutionary algorithms and other metaheuristics in water resources

H.R. Maier;Z. Kapelan;J. Kasprzyk;J. Kollat.
Environmental Modelling and Software (2014)

516 Citations

Evolutionary multiobjective optimization in water resources: The past, present, and future

Patrick M. Reed;David Hadka;Jonathan D. Herman;Joseph R. Kasprzyk.
Advances in Water Resources (2013)

465 Citations

Many objective robust decision making for complex environmental systems undergoing change

Joseph R. Kasprzyk;Shanthi Nataraj;Patrick M. Reed;Robert J. Lempert.
Environmental Modelling and Software (2013)

390 Citations

Comparing state-of-the-art evolutionary multi-objective algorithms for long-term groundwater monitoring design

J.B. Kollat;P.M. Reed.
Advances in Water Resources (2006)

344 Citations

Comparing sensitivity analysis methods to advance lumped watershed model identification and evaluation

Y. Tang;Patrick Reed;Thorsten Wagener;K. van Werkhoven.
Hydrology and Earth System Sciences Discussions (2006)

325 Citations

How effective and efficient are multiobjective evolutionary algorithms at hydrologic model calibration

Y Tang;P Reed;Thorsten Wagener.
Hydrology and Earth System Sciences (2005)

286 Citations

How should robustness be defined for water systems planning under change

Jonathan D. Herman;Patrick M. Reed;Harrison B. Zeff;Gregory W. Characklis.
Journal of Water Resources Planning and Management (2015)

251 Citations

Diagnostic assessment of search controls and failure modes in many-objective evolutionary optimization

David Hadka;Patrick Reed.
Evolutionary Computation (2012)

241 Citations

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Best Scientists Citing Patrick M. Reed

Thorsten Wagener

Thorsten Wagener

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Holger R. Maier

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Andrea Castelletti

Politecnico di Milano

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Dragan Savic

University of Exeter

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Klaus Keller

Pennsylvania State University

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Murugesu Sivapalan

University of Illinois at Urbana-Champaign

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Hoshin V. Gupta

Hoshin V. Gupta

University of Arizona

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Barbara S. Minsker

Barbara S. Minsker

Southern Methodist University

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Graeme C. Dandy

Graeme C. Dandy

University of Adelaide

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Zoran Kapelan

Zoran Kapelan

Delft University of Technology

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Jim W. Hall

Jim W. Hall

University of Oxford

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Angus R. Simpson

Angus R. Simpson

University of Adelaide

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Anthony J. Jakeman

Anthony J. Jakeman

Australian National University

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Martyn P. Clark

Martyn P. Clark

University of Saskatchewan

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Jim Freer

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Bithin Datta

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