Abstract
Aiming at the current BP neural network model for surface reconstruction, it is sensitive to the initial weight and threshold, easy to fall into the local minimum value, and the reconstruction accuracy is not high. The CS-BP surface reconstruction algorithm is proposed. Firstly, the cuckoo search algorithm is used to optimize the weight and threshold of BP model for the first time, and then the improved BP algorithm is used to further optimize, finally, the surface reconstruction model based on CS-BP neural network is established. Compared with the reconstruction results based on BP algorithm, quadratic fitting algorithm and Wolf neural network algorithm model, it is proved that the idea of using cuckoo algorithm to optimize BP model to construct surface reconstruction model is feasible, and cuckoo algorithm, like other swarm intelligence algorithms, can effectively improve the efficiency of BP surface reconstruction model.
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