A Method for Solving Ill-Posed Problems with Fuzzy Prior Information
Abstract This paper uses fuzzy sets to describe the fuzzy priori information of the unknown parameter vector based on the fuzzy theory, which is included in the mathematical model in the form of constraint conditions.The adjustment model with fuzzy prior information is given.The new adjustment criterion is established by using the normal fuzzy number, and proposes a new adjustment algorithm with fuzzy priori information. The new method can effectively solve the ill-posed problem of normal equations in surveying adjustment.The error analysis shows that the new method is better than the least squares estimation, the truncated singular value method and ridge estimation.
Key words :
fuzzy set
membership function
fuzzy priori information
ill-posed problem
Cite this article:
ZHAO Zhe,ZUO Tingying,SONG Yingchun. A Method for Solving Ill-Posed Problems with Fuzzy Prior Information[J]. jgg, 2018, 38(5): 524-528.
ZHAO Zhe,ZUO Tingying,SONG Yingchun. A Method for Solving Ill-Posed Problems with Fuzzy Prior Information[J]. jgg, 2018, 38(5): 524-528.
URL:
http://www.jgg09.com/EN/ OR http://www.jgg09.com/EN/Y2018/V38/I5/524
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