In　this　paper,　a　method　using　neural　network　for　optimizing　the　grading　ring　of　±1100kV　ultra-high　voltage　direct　current　(UHVDC)　wall　bushing　is　presented.　Firstly,　the　finite　element　method　(FEM)　is　applied　to　calculate　the　electric　field　distribution　along　hollow　insulator　surface　with　various　pipe　diameter,　ring　diameter　and　installation　position　of　the　grading　ring　and　the　optimal　goal　is　set　according　to　the　FEM　numerical　results.　Then　the　neural　network　model　is　built　and　trained　with　L-　M　algorithm　using　300　sets　of　data　calculated　by　the　method　of　parametric　scanning.　Finally,　the　parameters　of　grading　ring　are　optimized　according　to　the　neural　network　fitting　results.　The　optimized　grading　ring　uniforms　the　electric　field　distribution　along　the　hollow　insulator　surface.　This　paper　can　provide　a　reference　on　structural　design　of　UHVDC　wall　bushing.　©　2018　IEEE.