| 赵铁峰,陈显.基于粒子群算法的水文地质参数求解研究[J].矿产勘查,2020,11(11):2491-2494 |
| 基于粒子群算法的水文地质参数求解研究 |
| Research on solving hydrogeological parameters based on particle swarm optimization |
| 投稿时间：2020-04-28 |
| DOI： |
| 中文关键词: 地下水 水文地质 参数求解 粒子群算法 水文地质 |
| 英文关键词: groundwater, hydrogeology, parameter solution, particle swarm optimization, hydrogeological parameters |
| 基金项目: |
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| 摘要点击次数: 1550 |
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| 中文摘要: |
| 为了提高求解割离井公式中水文地质参数的速度和精度,研究粒子群算法的适用性。本文将观测出水量与理论出水量的偏差平方和作为目标函数,利用粒子群算法反求割离井公式中水文地质参数给水度μ和渗透系数K,并将其计算结果与直线图解法、试算法和配线法计算结果进行对比分析。结果表明,粒子群算法的精度最高且在计算过程中无须人工干预,不受主观影响。粒子群算法在水文地质参数求解计算中具有较好的适用性和应用价值。 |
| 英文摘要: |
| In order to improve the speed and accuracy of solving hydrogeological parameters in the formula of isolated wells, the applicability of particle swarm optimization is studied. In this paper, the square sum of the deviations between the observed water quantity and the theoretical water quantity is used as the objective function, and the particle swarm algorithm is used to inversely calculate the hydrogeological parameter water supply μ and the permeability coefficient K in the cut-off well formula, and the calculation results are compared with the straight line graphic method and trial The calculation results of the algorithm and wiring method are compared and analyzed. The results show that the particle swarm optimization algorithm has the highest accuracy and does not require human intervention in the calculation process and is not subjectively affected. Particle swarm optimization has good applicability and application value in calculating hydrogeological parameters. |
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