31 citations as recorded by crossref.

1. Echo Frequency Estimation Technology for Passive Surface Acoustic Wave Resonant Sensors Based on a Genetic Algorithm Y. Wu et al. https://doi.org/10.3390/s23239401
2. Positive- and negative-feedback regulations coordinate the dynamic behavior of the Ras-Raf-MEK-ERK signal transduction pathway S. Shin et al. https://doi.org/10.1242/jcs.036319
3. Optimization of snow-related parameters in the Noah land surface model (v3.4.1) using a micro-genetic algorithm (v1.7a) S. Lim et al. https://doi.org/10.5194/gmd-15-8541-2022
4. Parameter estimations of a storm surge model using a genetic algorithm S. You et al. https://doi.org/10.1007/s11069-011-9900-y
5. Parameterization and application of storm surge/tide modeling using a genetic algorithm for typhoon periods S. You et al. https://doi.org/10.1007/s00376-011-0113-9
6. A micro-genetic algorithm (GA v1.7.1a) for combinatorial optimization of physics parameterizations in the Weather Research and Forecasting model (v4.0.3) for quantitative precipitation forecast in Korea S. Park & S. Park https://doi.org/10.5194/gmd-14-6241-2021
7. Climate change over the high-mountain versus plain areas: Effects on the land surface hydrologic budget in the Alpine area and northern Italy C. Cassardo et al. https://doi.org/10.5194/hess-22-3331-2018
8. Modeling Chaotic Behavior of Chittagong Stock Indices S. Banik et al. https://doi.org/10.1155/2012/410832
9. Geostatistical assessment of warm-season precipitation observations in Korea based on the composite precipitation and satellite water vapor data S. Park et al. https://doi.org/10.5194/hess-22-3435-2018
10. Optimization of typhoon-wave parameterization schemes using the SWAN model coupled with a genetic algorithm Y. Wu et al. https://doi.org/10.3389/fmars.2026.1912747
11. Parameterization of a coupled CO2 and H2O gas exchange model at the leaf scale of Populus euphratica G. Zhu et al. https://doi.org/10.5194/hess-14-419-2010
12. Combinational Optimization of the WRF Physical Parameterization Schemes to Improve Numerical Sea Breeze Prediction Using Micro-Genetic Algorithm J. Yoon et al. https://doi.org/10.3390/app112311221
13. Improving the Asian dust storm prediction using WRF-Chem through combinational optimization of physical parameterization schemes J. Yoon et al. https://doi.org/10.1016/j.atmosenv.2024.120461
14. Improvement of typhoon rainfall prediction based on optimization of the Kain-Fritsch convection parameterization scheme using a micro-genetic algorithm J. Zhu et al. https://doi.org/10.1007/s11707-019-0798-0
15. Uncertainty reduction in quantitative precipitation prediction by tuning of Kain–Fritch scheme input parameters in the WRF model using the simulated annealing optimization method M. Afshar et al. https://doi.org/10.1002/met.1919
16. A genetic algorithm based nonlinear grey Bernoulli model for output forecasting in integrated circuit industry L. Hsu https://doi.org/10.1016/j.eswa.2009.11.068
17. Assessing optimal set of implemented physical parameterization schemes in a multi-physics land surface model using genetic algorithm S. Hong et al. https://doi.org/10.5194/gmd-7-2517-2014
18. Evolutionary Algorithm-Based Error Parameterization Methods for Data Assimilation Y. Bai & X. Li https://doi.org/10.1175/2011MWR3641.1
19. Assessment of the Microphysics and Cumulus Parameterization Schemes in WRF for Simulating the Heavy Rainfall Event on 8 August 2022 in South Korea M. Yu et al. https://doi.org/10.1007/s13143-026-00448-5
20. Knowledge-guided Genetic Algorithm for input parameter optimisation in environmental modelling K. Wendt et al. https://doi.org/10.1016/j.procs.2010.04.152
21. Empirical values and assumptions in the convection schemes of numerical models A. Villalba-Pradas & F. Tapiador https://doi.org/10.5194/gmd-15-3447-2022
22. Quantitative Precipitation Forecast of a Tropical Cyclone through Optimal Parameter Estimation in a Convective Parameterization X. Yu et al. https://doi.org/10.2151/sola.2013-009
23. Parameter Estimation in Cellular Radiation Effects Using PSO-SQP and GA-SQP Hybrid Methods D. Alzahrani et al. https://doi.org/10.1007/s12539-025-00736-0
24. Estimation of a logistic regression model by a genetic algorithm to predict pipe failures in sewer networks A. Robles-Velasco et al. https://doi.org/10.1007/s00291-020-00614-9
25. Development of a coupled genetic algorithm and empirical typhoon wind model and its application Y. Gong et al. https://doi.org/10.1016/j.oceaneng.2022.110723
26. Solar radiation transfer and performance analysis of an optimum photovoltaic/thermal system J. Zhao et al. https://doi.org/10.1016/j.enconman.2010.09.032
27. Development of a simple unified volatility-based scheme (SUVS) for secondary organic aerosol formation using genetic algorithms A. Xia et al. https://doi.org/10.5194/acp-11-6185-2011
28. Assessment of MME methods for seasonal prediction using WMO LC‐LRFMME hindcast dataset G. Kim et al. https://doi.org/10.1002/joc.6858
29. A new multimodel ensemble method using nonlinear genetic algorithm: An application to boreal winter surface air temperature and precipitation prediction J. Ahn & J. Lee https://doi.org/10.1002/2016JD025151
30. Handling error propagation in sequential data assimilation using an evolutionary strategy Y. Bai et al. https://doi.org/10.1007/s00376-012-2115-7
31. Estimation of parameters of a biochemically based model of photosynthesis using a genetic algorithm Y. SU et al. https://doi.org/10.1111/j.1365-3040.2009.02036.x