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591 |
Operation Policies through Dynamic Programming and Genetic Algorithms, for a Reservoir with Irrigation and Water Supply Uses
Enthalten in Water resources management Bd. 35, 12.3.2021, Nr. 5, date:3.2021: 1573-1586
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592 |
Optimal operation of Mula reservoir with combined use of dynamic programming and genetic algorithm
Enthalten in Sustainable Water Resources Management Bd. 2, 20.11.2015, Nr. 1, date:3.2016: 1-12
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593 |
Optimisation of contribution of candidate parents to maximise genetic gain and restricting inbreeding using semidefinite programming (Open Access publication)
Enthalten in Genetics, selection, evolution Bd. 39, 11.1.2007, Nr. 1, date:2.2007: 1-23
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594 |
Optimization of a multiple reservoir system operation using a combination of genetic algorithm and discrete differential dynamic programming: a case study in Mae Klong system, Thailand
Enthalten in Paddy and water environment Bd. 3, 12.2.2005, Nr. 1, date:3.2005: 29-38
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595 |
Optimizationof neural network architecture using genetic programming improvesdetection and modeling of gene-gene interactions in studies of humandiseases
Enthalten in BMC bioinformatics Bd. 4, 07.7.2003, Nr. 1, date:12.2003: 1-14
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596 |
Optimized injection-molding process for thin-walled polypropylene part using genetic programming and interior point solver
Enthalten in The international journal of advanced manufacturing technology Bd. 124, 23.11.2022, Nr. 1-2, date:1.2023: 297-313
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597 |
Optimizing agents with genetic programming: an evaluation of hyper-heuristics in dynamic real-time logistics
Enthalten in Genetic programming and evolvable machines Bd. 19, 6.4.2017, Nr. 1-2, date:6.2018: 93-120
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598 |
Parallel evolution using multi-chromosome cartesian genetic programming
Enthalten in Genetic programming and evolvable machines Bd. 10, 20.10.2009, Nr. 4, date:12.2009: 417-445
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599 |
Pareto Optimal Multigene Genetic Programming for Prediction of Longitudinal Dispersion Coefficient
Enthalten in Water resources management Bd. 33, 24.1.2019, Nr. 3, date:2.2019: 905-921
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600 |
Performance assessment of genetic programming (GP) and minimax probability machine regression (MPMR) for prediction of seismic ultrasonic attenuation
Enthalten in Earthquake science Bd. 26, 30.10.2013, Nr. 2, date:4.2013: 147-150
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