Feasibility analysis of the use of binary genetic algorithms as importance samplers application to a 1-D DC resistivity inverse problem

DOI10.1007/s11004-008-9151-yzbMath1142.86009OpenAlexW2049523962WikidataQ57607440 ScholiaQ57607440MaRDI QIDQ934750

B. E. Eshmatov

Publication date: 30 July 2008

Published in: Mathematical Geosciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11004-008-9151-y

zbMATH Keywords

Monte Carlo methodsGenetic algorithmsInverse problemsVertical electrical soundings

Mathematics Subject Classification ID

Monte Carlo methods (65C05) Learning and adaptive systems in artificial intelligence (68T05) Inverse problems in geophysics (86A22)

Related Items (4)

Estimating intrinsic formation constants of mineral surface species using a genetic algorithm ⋮ Enhancing slope stability prediction using fuzzy and neural frameworks optimized by metaheuristic science ⋮ Exploratory factor analysis of wireline logs using a float-encoded genetic algorithm ⋮ The curse of dimensionality in inverse problems

Uses Software

• Genocop

Cites Work

• Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
• Resolution analysis of general inverse problems through inverse Monte Carlo sampling
• Resolution of seismic waveform inversion: Bayes versus Occam
• Monte Carlo analysis of inverse problems
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