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In order to explore the establishment of a nonlinear network security situational awareness model based on random forest in the context of big data, a multi-level network security knowledge system evaluation model based on random forest is proposed. This article proposes a multi-level CSSA analysis system and then uses random memory algorithm to create a CSSA evaluation model. Also, it proposes a CSSA multi-level analysis framework and then uses random forest algorithm to build a CSSA evaluation model. A random vector distribution of the same values is used for all forest trees. In this article, the interval [0,1] is used to quantitatively describe the weight of the security level. The training sample ratio of test samples is 110:40, in order to predict the security of the network, the prediction of knowledge is closer to the true value, and the complexity of multi-level security is predicted. Use unusual forests. The tree returns the most recommended part, which is a more realistic assessment of network security. The experimental results show that considering the network security situation, the prediction performance of this method is closer to the actual value, and the performance is better than the other two methods. Therefore, perception of multi-level security situations can be effectively predicted using random access memory. It is proved that random forest is faster and more efficient in network security.

Background: Transurethral split of the prostate (TUSP) is effective in treating benign prostatic hyperplasia (BPH). However, there is still a lack of research focusing on the optimal target population for TUSP. This study aimed to compare the efficacy of TUSP in patients with different prostate volumes or ages., Methods: The study was a multicenter retrospective study. The outcomes of TUSP in BPH patients with different prostate volumes or different ages were compared. A total of 439 patients were included in the study. Patients were divided into two groups according to prostate volume, with a cut-off value of 50 mL. Similarly, the cut-off value for the age groups was 70 years. Baseline patient characteristics and perioperative outcomes were recorded. Follow-up was performed at 1, 6, and 12 months after surgery., Results: The mean age of the patients was 73.4 years, and the mean prostate volume was 51.2 mL. At 12-month follow-up after TUSP treatment, the patients' International Prostate Symptom Scores (IPSS), quality of life (QoL) scores, and postvoid residual (PVR) volumes decreased significantly, while peak urinary flow rate (Qmax) increased significantly. Intraoperative hemoglobin (Hb) reduction was significantly lower in the small volume group than in the large volume group. The incidence of postoperative urinary urgency and transient incontinence was lower in the small volume group. IPSS score, PVR, and Qmax in the small volume group showed more remarkable changes at several time points compared to the preoperative period. Postoperative pain scores were higher in the small volume group than in the large volume group. There were no differences between the two groups in terms of long-term complications. The younger group showed greater variation in PVR and Qmax at some time points but less variation in QoL than the older group., Conclusions: TUSP is overall safe and effective in treating BPH. This study showed differences in the outcomes of TUSP in treating different prostate volumes or ages of BPH patients. The optimal surgical approach for BPH patients might be selected clinically based on a combination of prostate volume or patient age., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tau.amegroups.com/article/view/10.21037/tau-21-1138/coif). The authors have no conflicts of interest to declare., (2022 Translational Andrology and Urology. All rights reserved.)