基于机器学习算法和数据分析技术的AI智能巡检识别系统应用研究

在国家社会经济快速发展的进程中,变电站作为电网系统运行的核心环节,其相关技术设备日益增多,对系统运维维护管理工作模式要求也越来越高.因此如何采用现代化技术理念构建智能巡检识别系统,成为新时期电网领域改革探索的主要课题.文章在了解机器学习算法和数据分析技术的相关概念后,根据机器学习算法和数据分析技术,构建人工智能化的变电站巡检识别系统,并通过实验验证系统设计性能及技术算法应用优势,以此提高我国电网行业的监管水平.

一种基于数据驱动及智能算法的锅炉燃烧优化系统和装置

本专利公开了一种基于数据驱动及智能算法锅炉燃烧的优化系统,方法和装置.其中,该优化系统包括数据管理系统,智能优化系统,显示系统,通过对大量的历史运行数据进行数据挖掘,获得各工况的最佳运行方式,建立含锅炉运行特征和规律的最佳案例知识库.通过智能优化系统对锅炉运行实时数据进行优化,获得燃烧优化指令,传送给显示系统显示,并反馈给控制系统.本专利充分利用现有数据资源,实现燃烧指令的优化调节,可解决在现有控制系统下锅炉可能在非最佳运行曲线范围内运行等技术问题.

生成式人工智能与图书馆阅读推广的算法歧视

Under the new trend of generative artificial intelligence (AI) being widely used in library services, the issue of algorithmic discrimination in the process of reading promotion has attracted increasing attention. Through semi structured interviews with 10 libraries in Nanjing, this study systematically identified the characteristics, manifestations, causes and impacts of algorithmic discrimination under generative AI. The study finds that algorithmic discrimination presents the characteristics of group tendency, content bias, and functional accessibility, and the main reasons for discrimination are technical limitations, data bias, and lack of system, which will have a diverse impact on readers' reading behavior, collection resource utilization, and social culture. Based on the above findings, this study proposes to effectively improve the fairness and inclusiveness of generative AI in library reading promotion and ensure users' equal reading opportunities and information access rights by constructing a multi-party collaborative governance mechanism, optimizing the design of recommendation algorithms, strengthening readers' digital literacy education, and improving the AI ethics review mechanism.