Intelligent Time-Depth Alignment of Synthetic Seismograms: Optimizing Dynamic Time Warping with a Genetic Algorithm

Key Points

• Alignment precision improved by 0.91% through adaptive window parameter optimization, adjusting to local features.
• DTW distance decreased from 2.19 to 2.17, indicating effective performance at a window size of 783.
• Utilization of genetic algorithm with dynamic mutation and diversity injection to optimize the alignment process.
• Increasing window size beyond optimal leads to higher computational load without improved accuracy.

Abstract