A　novel　hybrid　learning　algorithm　based　on　a　evolutionary　programming　to　design　a　growing　fuzzy　neural　network,　named　self-organizing　fuzzy　neural　network　based　on　evolutionary　programming,　to　implement　Takagi-Sugeno(TS)　type　fuzzy　models　is　proposed　in　this　paper.　Construct　and　parameters　of　the　fuzzy　neural　network　is　trained　by　evolutionary　algorithms.　Simulation　results　demonstrate　that　a　compact　and　high　performance　fuzzy　rule　base　can　be　constructed.　Comprehensive　comparisons　with　other　approach　show　that　the　proposed　approach　is　superior　over　other　in　terms　of　learning　efficiency　and　performance.　©　2010　IEEE.