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Abstract

Summary

Since the beginning of the nineteenth century, a significant evolution in optimization theory has been noticed. This paper introduces a new technique termed as Iterative Particle Swarm Optimization which is an improved version of Particle Swarm Optimization (PSO). In this paper we have shown the application of Iterative Particle Swarm Optimization for the inversion of reflected wave travel time data to derive P wave velocity and thickness of each layer of the assumed four layered Earth model. The performance of Iterative PSO has also been compared with standard PSO for noise free data sets. The search space is kept same for both the inversion techniques. The comparison demonstrates that Iterative PSO shows much better convergence than standard PSO. The inverted model parameters were found to be independent of the search space, thereby showing the robustness of the algorithm.

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/content/papers/10.3997/2214-4609.201601277
2016-05-31
2019-12-08
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References

  1. Agarwal, A., Soloman, J., Srivastava, S.
    [2015] Fitness Distance Ratio Based Particle Swarm Optimization - For Stochastic Inversion of 1–D Post stack Seismic Data. 77th EAGE Conference & Exhibition Student Programme, 2015.
    [Google Scholar]
  2. Sain, K., and Kaila, K.L.
    [1994] Direct calculation of interval velocities and layer thicknesses from seismic wide angle reflection times. Geophys.J.Int, 125, 30–38.
    [Google Scholar]
  3. Clerc, Ma.
    [2008] Why does it work?International Journal of Computational Intelligence Research.
    [Google Scholar]
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