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The curve fitting of XGH02 macromolecule carbon hygristor used in digital sondes is studied, based on the model of RBF (Radial Basis Function) neural network. Compared with the traditional method of curve fitting, a more precise model of sensor and error calibration is presented. The training and testing of the RBF neural network the model with training and testing samples indicates that the model of the RBF neural network can improve the accuracy of humidity resistance effectively, and the maximum error of measurement is 2.0298% (RH), which is smaller than that of the existing formula.