A multipopulation genetic algorithm to solve the inverse problem in hydrogeology

By D. Karpouzos, Frederick Delay, K. Katsifarakis, G. Marsily. 2001

69 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Environmental Engineering, Ocean Engineering

View Paper: https://www.semanticscholar.org/paper/912d4facf674333ab2310e98e6baf0d8ee76aef6

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Civil and Structural Engineering

1. Philippe Renard
2. Gregoire Mariethoz

In Environmental Engineering

1. Philippe Renard
2. Gregoire Mariethoz
3. Jef Caers
4. G. Mahinthakumar
5. Zhongmin Liang
6. Mohamed Sayeed
7. Niklas Linde
8. Muhammad Sahimi

In Ocean Engineering

1. Gregoire Mariethoz
2. Jef Caers
3. Philippe Renard
4. Muhammad Sahimi
5. Pejman Tahmasebi

Citations in the corpus

• Bayesian inverse problem and optimization with iterative spatial resampling (2010, methodology): “Genetic algorithms [Fraser, 1957; Goldberg, 1989] have been used for identifying structures in hydraulic conductivity fields [ Karpouzos et al., 2001 ].”
• Hybrid Genetic Algorithm—Local Search Methods for Solving Groundwater Source Identification Inverse Problems (2005, background): “2002), limited work has been done in the use of GAs for groundwater inverse problems (Aral and Guan 1996; Mahinthakumar et al. 1999; Karpouzos et al. 2001; Sayeed and Mahinthakumar 2002; Giacobbo et al. 2002).”
• A data-driven SVR model for long-term runoff prediction and uncertainty analysis based on the Bayesian framework (2018, background): “…algorithms (GA) are commonly used in complex optimization problems that require an appropriate function to perform the parameter-based adaptive search process and determine the optimal solution through genetic mechanisms such as selection, hybridization, and mutation (Karpouzos et al. 2001).”