Research on Risk Prediction and Early Warning of Human Resource Management Based on Machine Learning and Ontology Reasoning

Talent is the first resource, the development of the enterprise to retain key talent is essential, the main research is based on machine learning and ontological reasoning, human resources analysis and management risk prediction and early warning methods, first of all, according to the specific situation and the target case, through the calculation of the similarity of the concept name and attribute of the similarity assessment of the source case in the case library, the matching of knowledge-based employees of the company\u27s case for the similarity prediction and human resources management risk prediction research. Then, according to the evaluation results, we can find out the most suitable job matches in specific risk problems and situations. This is a solution to the target cases and criteria for companies to evaluate candidates. Second, we have successfully developed and implemented a prediction model that applies machine learning to the early warning study of risk prediction for HR management. The model is optimized with a cross-validation function, and the convergence of the model training is accelerated by the regularization of Newton\u27s iterative method. Finally, our prediction model achieved 82% yield. Ontological reasoning and machine learning are promising in human resource management risk prediction and warning, which is proved by the high accuracy rate verified by examples. Finally, we analyze the proposed results of HRM risk prediction and early warning to contribute to the improvement of risk control and suggest measures for possible risks

Advances in the Production of Theanine by Plants and Microorganisms

Theanine, a representative non-protein amino acid in tea, is one of the umami components of tea and a major factor in the formation of the unique flavor of tea leaves. In addition to its delicious taste, theanine has a variety of health functions and is used in the food supplement, pharmaceutical, nutraceutical, and cosmetic industries. This review briefly describes the physiological functions, application prospects, and production methods of theanine. The biosynthetic pathway of L-theanine in natural plants is also introduced. Finally, the microbial synthesis of L-theanine is divided into two major biosynthetic pathways guided by glutamine and glutamate according to the different substrates. According to the status, at present, of the microbial synthesis of L-theanine, the future development of microbial synthesis of L-theanine is prospected, in order to provide technical and theoretical basis for in-depth research on the industrial production of theanine