Adaptive trans-dimensional inversion of multimode dispersion curve based on slime mold algorithm

With the rise of low-cost and high-density observation system Distributed Acoustic Sensing (DAS), the effective utilization of high-mode surface wave becomes extremely important due to unique measuring method of DAS. To solve the interference of mode identification of dispersion curve and model dimension division on inversion results, we introduced the fitting degree of the dispersion curve, the model dimension, and the uncertainty estimation of the picked dispersion curve to construct a new objective function, and developed a strategy of adaptive trans-dimensional inversion of multimode dispersion curve based on slime mold algorithm (SMA). The research results show that our objective function can not only satisfy the fitting degree of dispersion curve, but also adaptively select the best model dimension, and does not depend on the mode identification of dispersion curve. Inversion strategy based on SMA algorithm has high flexibility, accuracy, stability, and practicality. Our method develops a new technology for dispersion curve inversion and provides a new idea for DAS system to realize low-cost and high-resolution city underground structure detection.