A New Multivalued Neural Network for Isomorphism Identification of Kinematic Chains

Abstract

A lot of methods have been proposed for the kinematic chain isomorphism problem. However, the tool is still needed in building intelligent systems for product design and manufacturing. In this paper, we design a novel multivalued neural network that enables a simplified formulation of the graph isomorphism problem. In order to improve the performance of the model, an additional constraint on the degree of paired vertices is imposed. The resulting discrete neural algorithm converges rapidly under any set of initial conditions and does not need parameter tuning. Simulation results show that the proposed multivalued neural network performs better than other recently presented approaches.

Similar Vertices and Isomorphism Detection for Planar Kinematic Chains Based on Ameliorated Multi-Order Adjacent Vertex Assignment Sequence

“…Due to the characteristics of the Fibonacci sequence, the sum of two groups with the same number of Fibonacci numbers is usually different. For example, for the first four items 1, 5, 21, 89 of the selected Fibonacci sequence, the sum of two repeatable pairs is carried out, and the result is 2,6,10,22,26,42,90,94,110,178; for the natural number 1, 2, 3, 4, the result is 2…”

“…Xiao et al [9] creatively combined ant colony algorithms and artificial immune algorithms to identify the isomorphism of KCs. Galán-Marín et al [10] first used the multi-value neural network method to identify the isomorphism of KCs. In the same year, Dargar et al [11] identified isomorphism by comparing the first-order and second-order adjacent component values of the KCs, but it cannot describe the uniqueness of each vertex in the topological graph.…”

Automatic Generation of N-Bar Planar Linkages Containing Sliders

“…Then, a complete atlas of KCs was presented. A simplified formulation of the isomorphism detection process was developed by Marin et al [30] using a neural network. A dividing and matching algorithm was proposed by Zeng et al [31] to detect the isomorphism using the adjacency matrix of KC and changing the order of vertices.…”

Improved high-order adjacent vertex assignment sequence for similarity vertices and isomorphism identification of planar kinematic chains

“…Ding and Huang [11][12][13][14] standardized topological graph according to certain rules, used the normal adjacency matrix to identify the KCs isomorphism, and developed the algorithm of related isomorphism identification. Galán-Marín et al [15] first used the multi value neural network method to identify the isomorphism of KCs. In the same year, Dargar et al [16] proposed to identify isomorphism by comparing the first-order and second-order adjacent component values of the KCs, but Improved high-order adjacent vertex assignment sequence for similarity vertices and isomorphism identification of planar kinematic chains •3• this method has the defect that it can't describe the uniqueness of each vertex in the topological graph.…”