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Electrolyte inclinometer is widely used to measure the horizontal displacement of earth-rock dam, face dam, rock slope, embankment, foundation pit and other structures. In order to eliminate the measurement error caused by ambient temperature change and measurement noise, the sensor temperature experiment is carried out, and the hardware itself, working environment, data acquisition three factors affecting the measurement error and temperature change are analyzed in detail. A precision compensation model based on variance compensation adaptive Kalman filter (AKF) and BP neural network (BPNN) is proposed. The results show that the mean square error of the horizontal displacement of the electrolytic inclinometer after compensation is reduced by more than 80% compared with that before compensation, which effectively reduces the error of calculating the horizontal displacement and greatly improves the measuring accuracy of the electrolytic inclinometer.