Search Strategy Optimization of Affine Propagation Clustering Algorithm - DONG Jing-wei; ZHANG Tian-qi; LIU Yang; YANG Guang (Journal of Harbin University of Science and Technology)
For multi floor fingerprint location, large scale fingerprint samples increase the complexity of the matching algorithm, which not only hinders the realtime performance of the system, but also increases the energy loss of the mobile terminal.According to the theory of affinity propagation clustering algorithm, we can reduce the amount of computation.Fingerprint sample search in complex environment usually adopts the binary search method, and the optimal parameters for bias results clustering quality of the coarse positioning stages, but this method takes a long time.In the calculation of quality guarantee under the premise, in order to improve the clustering speed, the coarse positioning stage and the matching process, and gives the method to improve the binary search method.The experimental results show that the clustering of the same sample space, the binary search method the optimized algorithm can reduce the number of iterations, improve the work efficiency of the system, and the use of the iteration time is 74.5% shorter than the traditional binary search method.