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.
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.
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.
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.
Evolutionary algorithms and other metaheuristics in water resources
H.R. Maier;Z. Kapelan;J. Kasprzyk;J. Kollat.
(2014)
Twenty-three unsolved problems in hydrology (UPH)–a community perspective
Günter Blöschl;Marc F.P. Bierkens;Antonio Chambel;Christophe Cudennec.
(2019)
Bayesian Networks and participatory modelling in water resource management
A. Castelletti;R. Soncini-Sessa.
(2007)
Benefits and challenges of using smart meters for advancing residential water demand modeling and management
A. Cominola;M. Giuliani;D. Piga;A. Castelletti.
(2015)
Water reservoir control under economic, social and environmental constraints
Andrea Castelletti;Francesca Pianosi;Rodolfo Soncini-Sessa.
(2008)
Integrated and Participatory Water Resources Management. Theory
Rodolfo Soncini-Sessa;Andrea Castelletti;Enrico Weber.
(2007)
An evaluation framework for input variable selection algorithms for environmental data-driven models
Stefano Galelli;Greer B. Humphrey;Holger R. Maier;Andrea Castelletti.
(2014)
Tree-based reinforcement learning for optimal water reservoir operation
A. Castelletti;S. Galelli;M. Restelli;R. Soncini-Sessa.
(2010)
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)
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)
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:
Cornell University
ETH Zurich
University of Adelaide
Polytechnic University of Milan
University of California, Davis
Polytechnic University of Milan
Lancaster University
Griffith University
University of Adelaide
Swiss Federal Institute for Forest, Snow and Landscape Research
National University of Singapore
Tokyo University of Science
Yokohama National University
Qingdao University
Jilin University
Carnegie Mellon University
University of Massachusetts Amherst
University of Minnesota
Ragon Institute of MGH, MIT and Harvard
Drexel University
Utrecht University
National Institutes of Health
University of Oxford
University of Minnesota
Johns Hopkins University
University of Liège