
To improve the accuracy of hydrogeological parameters, this paper conducts the simulationverification of golden sine algorithm (Gold-SA) algorithm by six standard test functions andcompares the simulation results with that of the particle swarm optimization (PSO) algorithm, andtaking two pumping test data as examples, optimizes two key parameters, i.e. transmissivitycoefficient and storage coefficient of theis formula by the Gold-SA algorithm and compares theresults with that of the PSO algorithm, wiring method and literature method. The results show thatthe Gold-SA algorithm has better optimization accuracy for the six selected standard testfunctions than the PSO algorithm, with better optimization accuracy and global search ability. Andthe optimization accuracy of Gold-SA algorithm for the transmissivity coefficient and storagecoefficient of the two examples is better than PSO algorithm, wiring method and literature method.Therefore, it is feasible and effective to apply the Gold-SA algorithm for the optimization ofhydrogeological parameters.
River, lake, and water-supply engineering (General), TC401-506, hydrogeological parameter, pumping test, golden sine algorithm, optimization
River, lake, and water-supply engineering (General), TC401-506, hydrogeological parameter, pumping test, golden sine algorithm, optimization
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
