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The present study proposes an alternate method based on genetic algorithm (GA) to estimate the subsurface lithologic parameters such as P-wave velocity, the S-wave velocity and the density for subsurface earth layers occurring at a particular location. These are useful parameters to discriminate lithology and help in detecting hydrocarbons from seismic data. However, estimation of the lithologic parameters...
In this paper, the authors propose a new evolutionary optimization technique i.e. modified biogeography-based optimization (MBBO). This technique is an improved version of BBO with each solution is directly encoded by floating point. BBO is a new bio-inspired and population based optimization algorithm for global optimization. The exploitation ability of BBO method is good but it lacks in exploration...
Particle Swarm Optimization (PSO) is arguably one of the most popular nature- inspired algorithms for real parameter optimization at present. The existing theoretical research on PSO is mostly based on the gbest (global best) particle topology, which usually is susceptible to false or premature convergence over multi-modal fitness landscapes. The present standard PSO (SPSO 2007) uses an lbest (local...
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