Analysis of DEM Gross Error Detection Method based on BP neural network
This paper expounds a DEM gross error detection method based on BP neural network.In order to reduce the misjudgment rate of the algorithm,the parameter of suspicion rate is added,so that the gross error judgment of a certain point can be based on the detection results of multiple regions.To determine the threshold of suspicion rate,bubble method,mean method,and median method were used respectively.The median method has better experimental results.The experiment was conducted with a suspicion rate threshold determined by the median,and the detection rate reached 94.1％,with a misjudgment rate of 31.5％.
deep learningBP neural networkdigital elevation modelgross error detection
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