Optimization of nonlinear geological structure mapping using hybrid neuro-genetic techniques

DOI10.1016/j.mcm.2011.07.012zbMath1235.90200OpenAlexW1984323876WikidataQ59280578 ScholiaQ59280578MaRDI QIDQ410021

I. Elamvazuthi, Pandian Vasant, Timothy Ganesan

Publication date: 15 April 2012

Published in: Mathematical and Computer Modelling (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.mcm.2011.07.012

zbMATH Keywords

nonlineargenetic programmingengineering problemsgeological structure mappinghybrid optimizationneuro-genetic programming

Mathematics Subject Classification ID

Applications of mathematical programming (90C90) Nonlinear programming (90C30) Seismology (including tsunami modeling), earthquakes (86A15) Computational methods for problems pertaining to geophysics (86-08)

Related Items (4)

Median based conversion of SGPA into percentage by cognitive methods ⋮ A penalty-free method with line search for nonlinear equality constrained optimization ⋮ A nonmonotone supermemory gradient algorithm for unconstrained optimization ⋮ Two-stage based ensemble optimization framework for large-scale global optimization

Cites Work

• The role of implied volatility in forecasting future realized volatility and jumps in foreign exchange, stock, and bond markets
• Neural networks and physical systems with emergent collective computational abilities.
• Neurons with graded response have collective computational properties like those of two-state neurons.
• Unnamed Item

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