Andreas Efstratiadis

Water Science and Technology · 2010–2018

A researcher in the Science corpus: 2 papers; trusts 24 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Water Science and Technology — 20 citations into it; #357 of 1,711 by trust here, #1,231 by citations
• Global and Planetary Change — 16 citations into it; #8,636 of 10,225 by trust here, #10,129 by citations
• Environmental Engineering — 10 citations into it; #1,907 of 5,479 by trust here, #4,165 by citations
• Ocean Engineering — 7 citations into it; #983 of 3,193 by trust here, #2,164 by citations
• Artificial Intelligence — 5 citations into it
• Computational Theory and Mathematics — 5 citations into it

Whom Andreas Efstratiadis trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Henrik Madsen
2. Keith Beven
3. Hoshin V. Gupta
4. Soroosh Sorooshian
5. Carlos Artemio Coello Coello
6. H. Choi
7. Catherine R. Moore
8. Misgana K. Muleta
9. Roger Moussa
10. Thorsten Wagener

Who trusts Andreas Efstratiadis overall

1. Aynom T. Teweldebrhan
2. J. Lamontagne
3. Misgana K. Muleta
4. John F. Burkhart
5. Caitline A. Barber
6. S. Pool
7. Martijn J. Booij
8. Richard M. Vogel
9. Thomas V. Schuler

Papers from Andreas Efstratiadis's perspective

Ordered by how strongly the researchers Andreas Efstratiadis trusts endorse each paper. Same corpus, a different order for every researcher.

1. The future of distributed models: model calibration and uncertainty prediction.
2. Multi-objective global optimization for hydrologic models
3. Genetic Algorithms in Search Optimization and Machine Learning
4. Bayesian recursive parameter estimation for hydrologic models
5. Genetic Algorithms in Search
6. Effective and efficient global optimization for conceptual rainfall‐runoff models
7. Toward improved calibration of hydrologic models: Combining the strengths of manual and automatic methods
8. Automatic calibration of a conceptual rainfall-runoff model using multiple objectives.
9. Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence
10. Parameter estimation in distributed hydrological catchment modelling using automatic calibration with multiple objectives

Their papers

• Timing the time of concentration: shedding light on a paradox (2018) — 60 citations
• One decade of multi-objective calibration approaches in hydrological modelling: a review (2010) — 476 citations