Design of Automatic Control System for Disinfection and Sterilization Method of Nursing Ventilator Based on PLC
Against the backdrop of rapid development in vascular science,automated diagnosis of carotid arteries has gained widespread attention from all sectors of society.However,in the face of complex environment,conventional methods will produce er-rors that cannot be ignored.In order to solve this problem,the feature set method is added to the extreme gradient lifting algorithm,and the weight factor is used to optimize the data mining technology to generate a fusion algorithm.The binary tree rule is added to the algorithm to generate a fusion algorithm.Finally,the experiment is carried out on Sclero data set and compared with three systems,such as Golden Sine.In one day,the power consumption of the converged system is 0.21 kW*h,which is the lowest among the four systems.After one month's diagnosis,the patients'carotid atherosclerosis scores were 2.8,3.0,3.1 and 3.4,respectively,which indicated that the proposed method had the best curative effect,and its blood flow rate score was 3.2,which indicated that the method had the highest adaptability to patients.The experimental results show that the fusion system proposed in this study has achieved the best results in experimental accuracy and diagnosis of patients'carotid hardness,and is suitable for diagnosis of patients with carotid atherosclerosis.
data miningweight factorlimit gradient lifting algorithmfeature setbifurcation tree rulecarotid atherosclero-sisautomatic diagnosis