Title
Self-evident Automated Proving Based on Point Geometry from the Perspective of Wu's Method Identity.
Abstract
The algebraic methods represented by Wu’s method have made significant breakthroughs in the field of geometric theorem proving. Algebraic proofs usually involve large amounts of calculations, thus making it difficult to understand intuitively. However, if the authors look at Wu’s method from the perspective of identity,Wu’s method can be understood easily and can be used to generate new geometric propositions. To make geometric reasoning simpler, more expressive, and richer in geometric meaning, the authors establish a geometric algebraic system (point geometry built on nearly 20 basic properties/formulas about operations on points) while maintaining the advantages of the coordinate method, vector method, and particle geometry method and avoiding their disadvantages. Geometric relations in the propositions and conclusions of a geometric problem are expressed as identical equations of vector polynomials according to point geometry. Thereafter, a proof method that maintains the essence of Wu’s method is introduced to find the relationships between these equations. A test on more than 400 geometry statements shows that the proposed proof method, which is based on identical equations of vector polynomials, is simple and effective. Furthermore, when solving the original problem, this proof method can also help the authors recognize the relationship between the propositions of the problem and help the authors generate new geometric propositions.
Year
DOI
Venue
2019
10.1007/s11424-019-8350-6
J. Systems Science & Complexity
Keywords
Field
DocType
Geometry algebra, point geometry, proof method based on identical equations, vector geometry, Wu’s method
Geometric reasoning,Euclidean vector,Mathematical optimization,Algebraic number,Algebra,Polynomial,Automated theorem proving,Mathematical proof,Geometric relations,Point (geometry),Mathematics
Journal
Volume
Issue
ISSN
32
1
1559-7067
Citations 
PageRank 
References 
0
0.34
1
Authors
3
Name
Order
Citations
PageRank
Jing-Zhong Zhang113716.54
Xicheng Peng232.08
Mao Chen300.68