Accurate identification of protein secondary structures is beneficial to understand three-dimensional structures of biological macromolecules. In this paper, a novel refined classification framework is proposed, which treats alpha-helix identification as a machine learning problem by representing each voxel in the density map with its Spherical Harmonic Descriptors (SHD). An energy function is defined to provide statistical analysis of its identification performance, which can be applied to all the α-helix identification approaches. Comparing with other existing α-helix identification methods for intermediate resolution electron density maps, the experimental results demonstrate that our approach gives the best identification accuracy and is more robust to the noise.

Many power distribution methods of microgrid (MG) are all limited by fixed structure of MG and mathematical model, which will be out of effect once the structure changes. In order to solve the above problems, this paper proposed an adaptive hierarchical control method considering generation cost. Firstly, the distributed generators (DGs) of MG are considered as multi-agent system, and the secondary controller based on finite-time theory is constructed. Secondly, the improved gray wolf optimization (IGWO) algorithm is used as the tertiary controller to dynamically optimize the rated power of DG, and the objective function and constraints are established. Thirdly, the adaptive virtual impedance is introduced to realize accurate power sharing and the closed-loop control is formed by combining the current loop and voltage loop controllers. Finally, by dynamically optimizing the rated power, the on-line real-time optimal power distribution of MG is achieved, and the stability of the system is proved by the theories of multi-agent consistency and finite-time stability. The control method proposed in this paper accelerates the convergence speed of MG, and the calculation results have high accuracy. At the same time, the flexibility and reliability of MG are improved. The simulation model is established in Matlab/Simulink environment, and the simulation results show that the method is effective.