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首页> 外文期刊>IEEE Journal of Oceanic Engineering >Using the adaptive simulated annealing algorithm to estimate ocean-bottom geoacoustic properties from measured and synthetic transmission loss data
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Using the adaptive simulated annealing algorithm to estimate ocean-bottom geoacoustic properties from measured and synthetic transmission loss data

机译:使用自适应模拟退火算法从实测和合成传输损耗数据估算海底地声特性

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摘要

This paper presents the results obtained using the adaptive simulated annealing (ASA) algorithm to invert the test cases from the Geoacoustic Inversion Techniques Workshop held in May 2001. The ASA algorithm was chosen for use in our inversion software for its speed and robustness when searching the geoacoustic parameter solution space to minimize the difference between the observed and the modeled transmission loss (TL). Earlier work has shown that the ASA algorithm is approximately 15 times faster than a modified Boltzmann annealing algorithm, used in prior versions of our TL inversion software, with comparable fits to the measured data. Results are shown for the synthetic test cases, 0 through 3, and for the measured data cases, 4 and 5. The inversion results from the synthetic test cases showed that subtle differences between range-dependent acoustic model version 1.5, used to generate the test cases, and parabolic equation (PE) 5.0, used as the propagation loss model for the inversion, were significant enough to result in the inversion algorithm finding a geoacoustic environment that produced a better match to the synthetic data than the true environment. The measured data cases resulted in better fits using ASTRAL automated signal excess prediction system TL 5.0 than using the more sophisticated PE 5.0 as a result of the inherent range averaging present in the ASTRAL 5.0 predictions.
机译:本文介绍了使用自适应模拟退火(ASA)算法对2001年5月举行的地声反演技术研讨会中的测试案例进行反演获得的结果。选择ASA算法用于我们的反演软件时,其搜索速度和鲁棒性都得到了提高。地球声学参数解空间,以最小化观测到的传输损耗(TL)与模型传输损耗之间的差异。早期的工作表明,ASA算法比以前的TL反转软件版本中使用的改进的Boltzmann退火算法快约15倍,并且与测量数据具有可比性。结果显示了0到3个综合测试用例以及4和5个测量数据的情况。综合测试用例的反演结果表明,范围相关的声学模型1.5版之间的细微差别用于生成测试在这种情况下,抛物线方程(PE)5.0用作反演的传播损失模型,其重要性足以使反演算法找到比真实环境与合成数据更匹配的地声环境。由于ASTRAL 5.0预测中存在固有的范围平均,因此使用ASTRAL自动化信号过剩预测系统TL 5.0所测得的数据情况比使用更复杂的PE 5.0更好。

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