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Barbara S. Minsker
Researcher at Southern Methodist University
Publications - 160
Citations - 4865
Barbara S. Minsker is an academic researcher from Southern Methodist University. The author has contributed to research in topics: Genetic algorithm & Cyberinfrastructure. The author has an hindex of 33, co-authored 158 publications receiving 4402 citations. Previous affiliations of Barbara S. Minsker include Indiana University – Purdue University Indianapolis & University of Illinois at Urbana–Champaign.
Papers
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Journal ArticleDOI
State of the Art for Genetic Algorithms and Beyond in Water Resources Planning and Management
John W. Nicklow,Patrick M. Reed,Dragan Savic,Tibebe Dessalegne,Laura J. Harrell,Amy Chan-Hilton,Mohammad Karamouz,Barbara S. Minsker,Avi Ostfeld,Abhishek Singh,Emily M. Zechman +10 more
TL;DR: This paper provides a comprehensive review of state-of-the-art methods and their applications in the field of water resources planning and management.
Journal ArticleDOI
Evolutionary algorithms and other metaheuristics in water resources
Holger R. Maier,Zoran Kapelan,Joseph R. Kasprzyk,Joshua B. Kollat,L. S. Matott,Maria da Conceição Cunha,Graeme C. Dandy,Matthew S. Gibbs,Edward Keedwell,Angela Marchi,Avi Ostfeld,Dragan Savic,Dimitri Solomatine,Jasper A. Vrugt,Aaron C. Zecchin,Barbara S. Minsker,Emily Barbour,George Kuczera,F. Pasha,Andrea Castelletti,Matteo Giuliani,Patrick M. Reed +21 more
TL;DR: Future EA-based applications to real-world problems require a fundamental shift of focus towards improving problem formulations, understanding general theoretic frameworks for problem decompositions, major advances in EA computational efficiency, and most importantly aiding real decision-making in complex, uncertain application contexts.
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Anomaly detection in streaming environmental sensor data: A data-driven modeling approach
David J. Hill,Barbara S. Minsker +1 more
TL;DR: The results indicate that a multilayer perceptron model of the data stream, coupled with replacement of anomalous data points, performs well at identifying erroneous data in this data stream.
Journal ArticleDOI
Striking the Balance: Long-Term Groundwater Monitoring Design for Conflicting Objectives
TL;DR: It is shown that high-order Pareto optimization holds significant potential as a tool that can be used in the balanced design of water resources systems.
Journal ArticleDOI
Designing a competent simple genetic algorithm for search and optimization
TL;DR: In this paper, theoretical relationships for population sizing and timescale analysis have been developed that can provide pragmatic tools for vastly limiting the number of parameter combinations that must be considered in a long-term groundwater monitoring design application.