In　this　research,　the　structure　optimized　BP-ANN　model　was　applied　to　simulate　the　permeate　flux　as　a　function　of　mixed　liquor　suspended,　temperature,　dissolved　oxygen,　hydraulic　retention　time,　transmembrane　pressure　and　operating　time　during　dead-end　microfiltration　of　activated　sludge　suspensions　and　its　supernatant　from　sequencing　batch　reactor　(SBR).　This　artificial　neural　network　approach　was　also　used　to　model　the　chemical　oxygen　demand　(COD)　concentration　of　effluent　from　SBR.　The　results　showed　that　the　structure　optimized　single　hidden　layer　neural　networks　was　able　to　accurately　simulate　the　dynamic　behavior　of　permeate　flux　and　the　COD　concentration　for　SBR　activated　sludge　process,　and　this　BP-ANN　model　possessed　higher　accuracy　than　that　of　C.　M.　Silva＇s　predictive　model　and　linear　multi-regression　model.　(C)　2011　Elsevier　B.V.　All　rights　reserved.