D-Index & Metrics Best Publications

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Engineering and Technology D-index 44 Citations 6,773 306 World Ranking 2825 National Ranking 81

Overview

What is she best known for?

The fields of study she is best known for:

  • Artificial intelligence
  • Machine learning
  • Hydrology

Andrea Castelletti spends much of her time researching Management science, Mathematical optimization, Process, Evolutionary algorithm and Robustness. Her studies in Management science integrate themes in fields like Systems management, Resource, Decision support system and Water resources. Andrea Castelletti performs multidisciplinary study on Water resources and Distribution system in her works.

The Mathematical optimization study combines topics in areas such as Curse of dimensionality and Reinforcement learning. Her work carried out in the field of Process brings together such families of science as Machine learning and Artificial intelligence. In her study, Andrea Castelletti carries out multidisciplinary Evolutionary algorithm and Key research.

Her most cited work include:

  • Evolutionary algorithms and other metaheuristics in water resources (337 citations)
  • Bayesian Networks and participatory modelling in water resource management (226 citations)
  • Twenty-three unsolved problems in hydrology (UPH)–a community perspective (144 citations)

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

Andrea Castelletti focuses on Hydropower, Mathematical optimization, Water resource management, Water resources and Drainage basin. Andrea Castelletti performs integrative study on Hydropower and Production. Her Mathematical optimization research is multidisciplinary, relying on both Control and Process.

Her research integrates issues of Structural basin and Hydrology in her study of Water resource management. Her Water resources research includes themes of Environmental economics, Management science, Environmental resource management and Water supply. Her Drainage basin study is concerned with Hydrology in general.

She most often published in these fields:

  • Hydropower (17.13%)
  • Mathematical optimization (15.17%)
  • Water resource management (13.48%)

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

  • Water resource management (13.48%)
  • Drainage basin (11.52%)
  • Hydropower (17.13%)

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

Andrea Castelletti mainly focuses on Water resource management, Drainage basin, Hydropower, Environmental economics and Environmental resource management. Her work deals with themes such as Structural basin, Flood myth and Hydrology, which intersect with Water resource management. She has included themes like Sediment trapping, Livelihood, Strategic planning and Irrigation in her Structural basin study.

Her study in Drainage basin is interdisciplinary in nature, drawing from both Global change and Water resources. Her research brings together the fields of Water conservation and Environmental economics. Her Environmental resource management research includes elements of Watershed, Diversion dam, Evapotranspiration and Water cycle.

Between 2018 and 2021, her most popular works were:

  • Twenty-three unsolved problems in hydrology (UPH)–a community perspective (144 citations)
  • Future drought risk in Africa: Integrating vulnerability, climate change, and population growth (51 citations)
  • Planning dam portfolios for low sediment trapping shows limits for sustainable hydropower in the Mekong (21 citations)

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

  • Artificial intelligence
  • Machine learning
  • Hydrology

Her scientific interests lie mostly in Hydropower, Multi-objective optimization, Control, Natural resource economics and Hydrometeorology. Andrea Castelletti integrates many fields in her works, including Hydropower, Structural basin, Livelihood, Water resource management, Sediment trapping and Strategic planning. Andrea Castelletti applies her multidisciplinary studies on Multi-objective optimization and Trade offs in her research.

The concepts of her Control study are interwoven with issues in Production, Optimal control, Data-driven, Environmental resource management and Flood myth. Her Natural resource economics study incorporates themes from Climate change mitigation, Urban water supply, Climate model and Water resources. Andrea Castelletti combines Hydrometeorology and Value in her research.

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

Evolutionary algorithms and other metaheuristics in water resources

H.R. Maier;Z. Kapelan;J. Kasprzyk;J. Kollat.
(2014)

601 Citations

Twenty-three unsolved problems in hydrology (UPH)–a community perspective

Günter Blöschl;Marc F.P. Bierkens;Antonio Chambel;Christophe Cudennec.
(2019)

363 Citations

Bayesian Networks and participatory modelling in water resource management

A. Castelletti;R. Soncini-Sessa.
(2007)

362 Citations

Benefits and challenges of using smart meters for advancing residential water demand modeling and management

A. Cominola;M. Giuliani;D. Piga;A. Castelletti.
(2015)

247 Citations

Water reservoir control under economic, social and environmental constraints

Andrea Castelletti;Francesca Pianosi;Rodolfo Soncini-Sessa.
(2008)

223 Citations

Integrated and Participatory Water Resources Management. Theory

Rodolfo Soncini-Sessa;Andrea Castelletti;Enrico Weber.
(2007)

189 Citations

An evaluation framework for input variable selection algorithms for environmental data-driven models

Stefano Galelli;Greer B. Humphrey;Holger R. Maier;Andrea Castelletti.
(2014)

185 Citations

Tree-based reinforcement learning for optimal water reservoir operation

A. Castelletti;S. Galelli;M. Restelli;R. Soncini-Sessa.
(2010)

179 Citations

Curses, Tradeoffs, and Scalable Management: Advancing Evolutionary Multiobjective Direct Policy Search to Improve Water Reservoir Operations

Matteo Giuliani;Andrea Francesco Castelletti;Francesca Pianosi;Emanuele Mason.
(2016)

177 Citations

Position Paper: A general framework for Dynamic Emulation Modelling in environmental problems

A. Castelletti;S. Galelli;M. Ratto;R. Soncini-Sessa.
Environmental Modelling and Software (2012)

174 Citations

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