Affiliation:
1. Harbin Institute of Technology
2. Daqing Petroleum Institute
Abstract
Aiming at hole filling in points cloud data reconstruction, a novel neural network
arithmetic was employed in abridged points cloud data surface reconstruction. Radial basis function
neural network and simulated annealing arithmetic was combined. Global optimization feature of
simulated annealing was employed to adjust the network weights, the arithmetic can keep the
network from getting into local minimum. MATLAB program was compiled, experiments on
abridged points cloud data have been done employing this arithmetic, the result shows that this
arithmetic can efficiently approach the surface with 10-4 mm error precision, and also the learning
speed is quick and hole filling algorithm is successful and the reconstruction surface is smooth.
Different methods have been employed to do surface reconstruction in comparison, the results
illustrate the error employed algorithmic proposed in the paper is little and converge speed is quick.
Publisher
Trans Tech Publications, Ltd.
Subject
Mechanical Engineering,Mechanics of Materials,General Materials Science
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