Abstract: The present disclosure discloses a high-safety ternary positive electrode material and a method for preparing the same; wherein the ternary positive electrode material has a chemical composition of Lia(NixCoyMn1-x-y)1-bMbO2-cAc, wherein 0.75?a?1.2, 0.75?x<1, 0<y?0.15, 1?x?y>0, 0?b?0.01, 0?c?0.2, M is one or more selected from the group consisting of Al, Zr, Ti, Y, Sr, W and Mg, and A is one or more selected from the group consisting of S, F and N; and CMn?(1?x?y)?0.07; CCo?y?0.05; 0?[CMn?(1?x?y)]/(CCo?y)?2.0. The ternary positive electrode material of the present disclosure is a high-nickel single crystal material with gradient concentration; it has the advantages of high capacity and high thermal stability, and the preparation method is simple, and is suitable for large-scale production.

Abstract: The present disclosure discloses a multiscale point cloud classification method. The method includes the following steps: acquiring 3D unordered point cloud data; performing feature extraction and classification on the acquired point cloud data using a pre-trained parallel classification network to obtain an output result, wherein the parallel classification network includes a plurality of basic networks with the same structures; and fusing the output results of the parallel network using a pre-trained deep Q network to obtain a final result of point cloud classification. The present disclosure can improve the accuracy and robustness of point cloud classification.