Improvement　of　fault　location　accuracy　plays　a　great　role　in　decreasing　repair　time　and　expediting　service　restoration.　However,　intricate　measurement　conditions　are　produced　by　some　factors　including　data　variation　and　noise.　These　factors　would　lead　to　nonconformity　in　reporting　samples　from　multiple　detectors　and　cause　errors　in　the　final　results　calculating.　To　improve　fault　location　accuracy　in　transmission　grids,　an　innovative　data　fusion　algorithm,　based　on　the　Adaptive　Fuzzy　Neural　Network　(AFNN)　mechanism,　is　proposed　in　this　paper.　In　the　model,　Fuzzy　Data　Fusion　(FDF)　mechanism　is　formed　and　serves　as　the　initial　fusion　to　estimate　the　correction　coefficient　of　Faulted　Traveling　Wave　Propagation　Speed　(FTWPS).　In　the　final　fusion,　Adaptive　Fuzzy-Neural-Network-based　Data　Fusion　Systems　(AFNN-DFSs)　are　trained　to　yield　the　final　fault　location　results　with　high　accuracy.　The　overall　procedure　of　the　proposed　fault　location　technique　is　constructed　using　PSCAD/EMTDC　and　MATLAB.　Besides,　the　feature　of　the　faulted　traveling　wave　is　extracted　by　using　Continuous　Wavelet　Transform　(CWT).　Finally,　case　studies　and　discussions　on　the　new　method,　based　on　AFNN-DFSs,　are　given　to　prove　the　advantages　of　the　novel　method　in　computational　accuracy.　©　2020　IEEE.