基于虚拟装配体绑定的产品层次化装配序列生成

装配是产品制造中的重要环节之一.计算机辅助装配顺序的生成为实施快速、灵活、优化的装配,提高装配质量和效率提供有力的支持.任务层次与分解方法的设计是层次任务网规划方法应用的关键技术.文中提出了一种基于虚拟装配体绑定的底层装配操作实施机制,在此基础上建立了产品装配序列生成的任务分解策略.装配实例表明,该方法在产品装配序列生成中具有建模层次清晰、任务分解策略易于制定、装配序列生成比较灵活的特点.     

基于人工智能的兵棋推演作战分析研究与设计

20世纪,随着计算机的出现,使得繁琐、严格的兵棋规则可以在计算机中处理,冯·莱斯威茨父子发明的兵棋迎来了新的春天。论文首先从战斗力度量、战斗结果裁判两方面详细分析了兵棋推演与其它战争分析方法的联系,并总结了兵棋推演应用于战争分析的实践意义。接着以兵棋推演为基础,介绍了相关的对策论、有信息的对抗搜索和局部优化搜索等人工智能技术。最后以一个战术想定为背景,详细阐述了设计兵棋系统时应用人工智能需要解决的数字化、博弈树生成和局面评估等问题。     

城市轨道交通安检系统智能判图模式研究与设计

为提升城市轨道交通安检系统判图效率及准确率,设计一种新颖的判图模式,将 AI(人工智能)图像识别技术与人工集中判图技术有效结合。首先针对逢液必检现状引入液体检测算法,避免对安全液体的开包查验,其次按安检品风险等级进行分类处理,最后结合 AI 置信度判断、人工抽检或必检判图对安检品进行判定。本判图模式可根据不同阶段下 AI 图像识别准确度和判图需求灵活调节 AI 介入深度,随着 AI 图像识别准确度的不断提升,逐渐从 AI 为辅、人工为主判图模式向 AI 为主、人工为辅的判图模式平滑渐进迭代,最终实现完全智能判图模式。通过案例分析可知,在不降低城市轨道交通车站安检水平的前提下,本判图模式可以进一步达到前端过检增速、后端降本增效的目的。     

基于百度云AI的自动售检票系统人脸识别应用可行性分析

人脸识别作为生物识别技术的重要分支,因其非接触性特点,在身份认证方面已经获得广泛应用。百度云AI作为智能云平台已经开放轻量级人脸识别和认证的应用服务。基于该服务不需要重复研发人脸识别算法,短期即可完成“刷脸”乘车环境搭建。分析了基于百度云AI(人工智能)技术快速建立轨道交通AFC(自动售检票)系统人脸身份识别应用场景的可行性。     

Progress and Perspective of Artificial Intelligence and Machine Learning of Prediction in Anesthesiology

Artificial intelligence (AI) has long been an attractive topic in medicine,especially in light of the rapid developments in digital and information technologies.AI has already provided some breakthroughs in medicine.With the assistance of AI,more precise models have been used for clinical predictions,diagnoses,and decision-making.This review defines the basic concepts of AI and machine learning (ML),and provides a simple introduction to certain frequently used algorithms in AI and ML.In addition,the review discusses the current common applications of AI and ML in the prediction of anesthesia conditions,including those for preoperative predictions of difficult airways,intraoperative predictions of adverse events and anesthetic effects,and postoperative predictions of vomiting and pain.The use of AI in anesthesiology remains in development,even without extensive promotion and clinical application;moreover,it has immense potential to maintain further development in the future.Finally,the limitations and challenges of AI development for anesthesia are also discussed,along with considerations regarding ethics and safety.     

基于1SDl548AI的IGBT驱动器设计

介绍了一种基于1SDl548AI的IGBT驱动器设计。对前级驱动电路、栅极电阻、过流和短路保护、补偿电容等进行了详细分析。试验证明该驱动器可用于大功率逆变场合,能很好地实现对IGBT模块的驱动和保护。     

Artificial intelligence for traffic signal control based solely on video images

Learning-based traffic control algorithms have recently been explored as an alternative to existing traffic control logics. The reinforcement learning (RL) algorithm is being spotlighted in the field of adaptive traffic signal control. However, no report has described the implementation of an RL-based algorithm in an actual intersection. Most previous RL studies adopted conventional traffic parameters, such as delays and queue lengths to represent a traffic state, which cannot be exactly measured on-site in real time. Furthermore, the traffic parameters cannot fully account for the complexity of an actual traffic state. The present study suggests a novel artificial intelligence that uses only video images of an intersection to represent its traffic state rather than using handcrafted features. In simulation experiments using a real intersection, consecutive aerial video frames fully addressed the traffic state of an independent four-legged intersection, and an image-based RL model outperformed both the actual operation of fixed signals and a fully actuated operation.     

统一理论——人工智能研究的新进展

人们一直认为结构、功能和行为是智能系统3个基本支柱,因此形成了人工智能理论的结构模拟、功能模拟和行为模拟三大学派。但是,这些研究留下许多问题：互相之间缺乏沟通,却常有“孰优孰劣”的争论。文中提出了一种全新的研究途径——智能生成的“机制方法”,希望从智能生成的共性机制人手探讨智能的本质。研究发现：在一般情形下,智能生成机制表现为“信息一知识一智能的转换”,由此引出了“知识理论”,并发现了知识的生态结构;更为有趣的是,人工智能的结构模拟、功能模拟、行为模拟3种理论在“机制方法”框架内得到了和谐完美的统一。这为智能科学技术的发展提供了新的理解和新的机会。     

人工智能背景下学习中心课堂的价值困境与突破路径

建构学习中心课堂是我国当今课堂教学改革的基本取向,人工智能为学习中心课堂带来了全新的机遇和挑战.从时空发展、学习资源以及学生个性发展三个方面审视人工智能下学习中心课堂的价值.揭示目前人工智能下学习中心课堂的困境,包括“工具价值大于教育价值——明显的技术主义倾向”、“学生主体大于教师主导——教师的主导性作用被轻视”以及“...