Laser induced breakdown spectroscopy (LIBS) combined with adaptive particle swarm optimization-based radial basis neural network (APSO-RBF) for rapid identification of soils from different regions

Traditional soil identification methods require a lot of time, while this paper proposes a combination of laser-induced breakdown spectroscopy (LIBS) and adaptive particle swarm optimization-based radial basis neural network (APSO-RBF), which is able to quickly and accurately classify soils from different regions, and the experimental results show that the classification accuracy in the test set reaches 99.8148%, which is verified by comparing with the backpropagation ( BP) algorithm, Adaptive Particle Swarm Optimization-Based Backpropagation (APSO-BP) algorithm and Radial Basis Neural Network (RBF) algorithm, which verifies the powerful classification performance of the model.