With　the　accumulating　of　the　strong　earthquakes　records,　it　becomes　practicable　to　achieve　the　more　accurate　attenuation　relationships.　Based　on　the　seismic　records　of　West　American,　the　Radial　Basis　Function　(RBF)　and　Back　Propagation　(BP)　artificial　neural　networks　model　are　respectively　constructed　for　three-dimensional　seismic　parameters　attenuation　relationship.　The　RBF　model　is　nice　fitting　for　the　training　data,　although　it　has　great　errors　on　other　tested　points.　While　the　BP　model　is　not　good　than　the　RBF　model　for　the　training　data,　it　possesses　a　better　consecutive　property　in　the　whole　area.　It　is　a　proper　neural　network　model　for　the　problem.　After　training　with　the　selected　records,　the　Neural　Networks　(NN)　shows　a　good　fitting　with　the　training　records.　And　it　is　easy　to　construct　three-dimensional　model　to　predict　the　attenuation　relationship.　In　order　to　demonstrate　the　efficiency　of　the　presented　methodology,　the　contrast　is　discussed　for　the　results　of　the　BP　model　and　three　typical　traditional　attenuation　formulae.　©　Springer-Verlag　Berlin　Heidelberg　2006.