基于改进型PPO算法的公寓安全预警模型

Apartment Security Alert Model Based On Improved PPO Algorithm

随着城市化的加速和公寓建筑的快速增长,确保居民的安全已成为当务之急。本文深入探讨了基于改进型近端策略优化(PPO)算法的公寓安全预警模型的开发。引入了一种新的深度学习架构,作为实时分析和预测潜在安全威胁的核心技术。实验结果表明,改进后的PPO算法在准确性、效率和响应时间方面明显优于传统方法。此外,该系统能够及时提供警报,确保公寓居民的安全。本文不仅强调了深度学习在安全和安防应用中的潜力,而且为智能生活环境领域的未来发展奠定了基础。

With the acceleration of urbanization and the rapid growth of apartment buildings,ensuring the safety of residents has become a top priority.This study delves into the development of an apartment safety warning model based on an improved PPO algorithm.We introduce a new deep learning architecture as the core technology for real-time analysis and prediction of potential safety threats.Experimental results show that the improved PPO algorithm significantly outperforms traditional methods in terms of accuracy,efficiency,and response time.Furthermore,the system can provide timely alerts to ensure the safety of apartment residents.This research not only emphasizes the potential of deep learning in safety and security applications but also lays the foundation for the future development of intelligent living environments.