Tracking Error Modeling of the Theodolite Based on GRNN Method

Abstract:

To meet the requirement of high tracking accuracy as well as develop more reasonable evaluation method, in this paper, the General Regression Neural Network (GRNN) has been applied to build the tracking error model of the theodolite. First, we analyze the nonlinear factors in the theodolite. Second, we discuss the principle of GRNN, including its structure, the function as well as its priors. Third, we build the tracking error model based on GRNN and verify the model through the different parameters. The result indicated that the network model based on GRNN has high accuracy and good generalization ability. It could instead the real system to a certain extent. The research in this paper has important value to the engineering practice.

• Periodical: Applied Mechanics and Materials (Volumes 121-126)
• Pages: 4870-4874
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.121-126.4870
• Online since: October 2011
• Authors: Miao Li, Hui Bin Gao
• Keywords: GRNN, Identified Model, Model Verification

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