Estimating the relationship between isoseismal area and earthquake magnitude by a hybrid fuzzy-neural-network method

DOI10.1016/S0165-0114(98)00293-0zbMath0964.86007OpenAlexW2037926052MaRDI QIDQ1125332

S. H. Smith

Publication date: 6 December 1999

Published in: Fuzzy Sets and Systems (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0165-0114(98)00293-0

zbMATH Keywords

earthquake engineeringartificial neural networksapproximate reasoningearthquake magnitudehybrid fuzzy neural networkinformation diffusion methodisoseismal area

Mathematics Subject Classification ID

Seismology (including tsunami modeling), earthquakes (86A15) Computational methods for problems pertaining to geophysics (86-08)

Related Items (1)

A diffusion-neural-network for learning from small samples

Cites Work

• Stochastic finite-state systems in control theory
• A computational approach to fuzzy quantifiers in natural languages
• Principle of information diffusion
• Application of Fuzzy Logic to Approximate Reasoning Using Linguistic Synthesis
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: Estimating the relationship between isoseismal area and earthquake magnitude by a hybrid fuzzy-neural-network method