An intelligent prediction model of epidemic characters based on multi-feature

The epidemic characters of Omicron(e.g.large-scale transmission)are significantly different from the initial variants of COVID-19.The data generated by large-scale transmission is important to predict the trend of epidemic characters.However,the re-sults of current prediction models are inaccurate since they are not closely combined with the actual situation of Omicron transmission.In consequence,these inaccurate results have negative impacts on the process of the manufacturing and the service industry,for example,the production of masks and the recovery of the tourism industry.The authors have studied the epidemic characters in two ways,that is,investigation and prediction.First,a large amount of data is collected by utilising the Baidu index and conduct questionnaire survey concerning epidemic characters.Second,theβ-SEIDR model is established,where the population is classified as Susceptible,Exposed,Infected,Dead andβ-Recovered persons,to intelligently predict the epidemic characters of COVID-19.Note thatβ-Recovered persons denote that the Recovered persons may become Sus-ceptible persons with probabilityβ.The simulation results show that the model can accurately predict the epidemic characters.

Cognitive mechanism related to line drawings and its applications in intelligent process of visual media： a survey

Line drawings, as a concise form, can be recognized by infants and even chimpanzees. Recently, how the visual system processes line-drawings attracts more and more attention from psychology, cognitive science and computer science. The neuroscientific studies revealed that line drawings generate similar neural actions as color photographs, which give insights on how to efficiently process big media data. In this paper, we present a comprehensive survey on line drawing studies, including cognitive mechanism of visual perception, computational models in computer vision and intelligent process in diverse media applications. Major debates, challenges and solutions that have been addressed over the years are discussed. Finally some of the ensuing challenges in line drawing studies are outlined.

Application of Depth Learning Algorithm in Automatic Processing and Analysis of Sports Images

With the rapid development of sports,the number of sports images has increased dramatically.Intelligent and automatic processing and analysis of moving images are significant,which can not only facilitate users to quickly search and access moving images but also facilitate staff to store and manage moving image data and contribute to the intellectual development of the sports industry.In this paper,a method of table tennis identification and positioning based on a convolutional neural network is proposed,which solves the problem that the identification and positioning method based on color features and contour features is not adaptable in various environments.At the same time,the learning methods and techniques of table tennis detection,positioning,and trajectory prediction are studied.A deep learning framework for recognition learning of rotating flying table tennis is put forward.The mechanism and methods of positioning,trajectory prediction,and intelligent automatic processing of moving images are studied,and the self-built data sets are trained and verified.

Intelligent Information Processing in Imaging Fuzes

In order to study the problem of intelligent information processing in new types of imaging fuze, the method of extracting the invariance features of target images is adopted, and radial basis function neural network is used to recognize targets. Owing to its ability of parallel processing, its robustness and generalization, the method can realize the recognition of the conditions of missile-target encounters, and meet the requirements of real-time recognition in the imaging fuze. It is shown that based on artificial neural network target recognition and burst point control are feasible.

Efficient pipelined flow classification for intelligent data processing in IoT

The packet classification is a fundamental process in provisioning security and quality of service for many intelligent network-embedded systems running in the Internet of Things(IoT).In recent years,researchers have tried to develop hardware-based solutions for the classification of Internet packets.Due to higher throughput and shorter delays,these solutions are considered as a major key to improving the quality of services.Most of these efforts have attempted to implement a software algorithm on the FPGA to reduce the processing time and enhance the throughput.The proposed architectures,however,cannot reach a compromise among power consumption,memory usage,and throughput rate.In view of this,the architecture proposed in this paper contains a pipelinebased micro-core that is used in network processors to classify packets.To this end,three architectures have been implemented using the proposed micro-core.The first architecture performs parallel classification based on header fields.The second one classifies packets in a serial manner.The last architecture is the pipeline-based classifier,which can increase performance by nine times.The proposed architectures have been implemented on an FPGA chip.The results are indicative of a reduction in memory usage as well as an increase in speedup and throughput.The architecture has a power consumption of is 1.294w,and its throughput with a frequency of 233 MHz exceeds 147 Gbps.

5^(th)International Conference on Intelligent Information Processing (IIP2008)

September 10 ~12 ,2008,Lyon,France The IIP conference series provides aforumfor engineers andscientistsin academia,university andindustryto present theirlatest researchfindings in any aspects of intelligent information processing.This ti me , we especially encourage papers on Knowledge Discovery , Knowledge Management ,Intelligent Agents , Machine Learning, Autonomic Reasoning etc.We also welcome papers that highlight successful modern applications of IIP,such as Biomedicine ,Bioinformatics ,e-Services ,e-Learning, Business Intelligence.IIP2008 attempts to meet the needs of a large and diverse community.

选煤厂重介质分选工艺智能化改造及应用

针对陕西某选煤厂入选煤质变化较大、集成化不高、智能化程度底等问题,结合煤炭行业智能化应用与发展趋势,通过对选煤工艺流程和洗选装备进行分析,以自动化为基础,准确拾取底层数据,建立生产模型,主要针对重介系统、浓缩系统等环节进行改造,提高了选煤厂生产的科学性和稳定性,实现了降本增效、安全生产。

全流程智能化成套设备的纺纱方案设计及技术特点

为呈现一个纺纱项目设计方案的基本过程和理念,以10万锭纺纱项目为例,详细介绍了环锭纺纱项目的工艺路径、设备配台方案、工程设计方案。基于项目运营智能化、制造数字化、装备智联化的总体要求,重点阐述了智能化纺纱工艺流程及主机设备的基本特点,以及全流程关键设备的技术与应用。认为:高度融合国产最新的先进智能棉纺成套装备、管理和控制系统,有助于提升纺纱全过程的自动化、信息化、智能化水平,实现工艺流、信息流、物流的全面集成。

数字化在酿酒生产过程中的应用及展望

从酿酒生产操作过程、窖池管控、生产工艺管控、能源管理、智慧工厂4个方面概述了数字化的应用和发展方向,肯定了数字化对白酒生产企业的发展和未来所起到的关键作用,为今后白酒行业的发展奠定了基础。

成套开关柜二次线生产工艺的智能化设计

为提高成套开关柜二次线生产质量和效率,降低人工成本及线材损耗量,通过增加在线传感器以及使用双线自动切换设备、切剥一体化设备、线号管智能化喷印设备,实现成套开关柜二次线生产的智能化。实践表明,生产线智能化后,人工成本降低约33.3%,线材损耗率降低11%,压接合格率提升至99%,每小时可加工1000条二次线。

平洞钻爆法开挖支护全工序机械化智能化施工技术

随着科学、技术、经济条件的改善,我国隧道施工机械化水平不断提高。在隧道施工中,全机械化施工的发展是未来隧洞施工的新方向,采用全机械化施工作业代替人工开挖作业,改善劳动条件。机械化施工作业不但能够提升施工效率,缩减工程工期,减少人工的体力劳动、确保施工人员的生命安全,而且可以保证施工质量,提高施工效益。同时机械化施工对实现工程施工质量标准化、提高隧洞信息化水平,促进隧道施工机械朝着更加规范、标准的方向发展。

汽车涂装车身缺陷识别及处理发展趋势探讨

详细阐述了常见的漆面外观缺陷种类,包括缩孔、砂痕、起泡等,分析其形成原因及对产品外观的影响。深入探讨智能识别技术,如图像采集、特征提取及识别算法等在漆面外观缺陷检测中的应用。对于识别出的缺陷,引入自动打磨/抛光处理技术,论述其工作原理、设备选型及工艺参数优化。通过试验对比不同处理方法的效果,验证自动打磨/抛光处理的优势。最后,展望未来涂装领域在漆面外观缺陷智能识别与自动打磨抛光处理方面的发展趋势,为提升涂装质量和生产效率提供理论支持与实践指导。

Intelligent Control and Maintenance Man-agement Integrated System Based on Multi-Agents for Coal-Preparation Plant

This paper discusses the progress of computer integrated processing （CIPS） of coal-preparation and then preserits an intelligence controlled production-process, device-maintenance and production-management system of coal- preparation based on multi-agents （IICMMS-CP）. The construction of the IICMMS-CP, the distributed network control system based on live intelligence control stations and the strategy of implementing distributed intelligence control system are studied in order to overcome the disadvantages brought about by the wide use of the PLC system by coaipreparation plants. The software frame, based on a Multi-Agent Intelligence Control and Maintenance Management integrated system, is studied and the implemention methods of IICMMS-CP are discussed. The characteristics of distributed architecture, cooperation and parallel computing meet the needs of integrated control of coal-preparation plants with large-scale spatial production distribution, densely-related processes and complex systems. Its application further improves the reliability and precision of process control, accuracy of fault identification and intelligence of production adjustment, establishes a technical basis for system integration and flexible production. The main function of the system has been tested in a coal-preparation plant to good effect in stabilizing product quality, improving efficiency and reducing consumption.

Investigation of system structure and information processing mechanism for cognitive skywave over-the-horizon radar

Based on the cognitive radar concept and the basic connotation of cognitive skywave over-the-horizon radar（SWOTHR）, the system structure and information processingmechanism about cognitive SWOTHR are researched. Amongthem, the hybrid network system architecture which is thedistributed configuration combining with the centralized cognition and its soft/hardware framework with the sense-detectionintegration are proposed, and the information processing framebased on the lens principle and its information processing flowwith receive-transmit joint adaption are designed, which buildand parse the work law for cognition and its self feedback adjustment with the lens focus model and five stages informationprocessing sequence. After that, the system simulation andthe performance analysis and comparison are provided, whichinitially proves the rationality and advantages of the proposedideas. Finally, four important development ideas of futureSWOTHR toward ＂high frequency intelligence information processing system＂ are discussed, which are scene information fusion, dynamic reconfigurable system, hierarchical and modulardesign, and sustainable development. Then the conclusion thatthe cognitive SWOTHR can cause the performance improvement is gotten.

煤矿智能化关键技术研究与实践

煤矿智能化是煤炭行业实现可持续发展的重要途径,为煤矿企业减人增效、安全生产提供有效保障,大数据、机器人、人工智能等新一代信息技术有力支撑了煤矿智能化建设。首先阐述了智慧矿山的设计思路,提出了智能化建设总体技术体系。然后,分析了通用异构型控制和数据处理平台、矿用巡检机器人技术、人工智能技术、故障诊断技术和智能穿戴等煤矿智能化关键技术的发展现状与趋势,梳理了智能化建设应用过程中存在的关键难题,并针对瓶颈问题提出了解决方法与未来发展趋势。研究基于模块化开发的通用异构型控制和数据处理平台,实现了底层终端的可重构和底层通信协议的统一,解决了数据孤岛问题;研究巡检机器人驱动模块监测、运动控制与精确定位等关键技术,基于多传感器融合技术实现机器人精确定位;研究人工智能技术在煤矿场景应用中缺少典型数据和与场景知识结合的问题,提出小样本学习技术有望推动人工智能技术在煤矿智能化领域的进一步落地应用;研究煤矿设备故障诊断技术,提出构建基于数据和知识混合驱动的设备故障诊断模型将有效解决过度维修和欠维修的问题;智能穿戴技术是解决井下关键岗位作业人员防护问题的关键,提出了由呼吸系统、传感监测系统、人机交互系统、语音显示系统组成的智能穿戴系统设计方案。最后,阐述了内蒙古神东天隆集团霍洛湾煤矿与内蒙古神东天隆集团武家塔露天煤矿智能化建设实践经验与阶段成果,为不同类型煤矿的智能化建设提供参考。

油气生产智能安全运维:内涵及关键技术

油气生产系统具有运维风险高、事故影响大的特点。随着信息化与工业化的深度融合,油气生产系统发展成互联互通、多领域交互的信息物理智能系统是行业发展的方向和必然选择。因此,为了避免或者减少油气生产过程中复杂多样、潜在未知的安全风险,提高油气生产系统安全性和可靠性,以提升生产效率,针对油气生产系统智能化过程中呈现出的安全问题,在智能安全运维技术关键要素基础上,结合油气生产行业典型生产场景,从运维角度进行了分析研究和体系构建。研究结果表明:(1)明确了智能安全运维技术的内涵,分析了智能安全运维技术的关键要素以及存在问题与挑战,构建了“1-2-3-4-5-6”油气生产系统智能安全运维技术体系,将6大关键技术赋能油气生产关键要素,实现了油气生产系统本质安全;(2)智能安全运维技术在油气生产上、中、下游的钻井开采、储存运输、炼油化工等典型生产场景中积极推进状态监测、健康管理、风险评估、智能预警等技术的应用实施;(3)针对数字化转型下油气生产系统特点,提出了未来将打造智能决策、主动预防、全面安全的智能安全运维技术,助力油气生产领域安全建设,推动了油气行业安全健康发展。结论认为,开展油气生产系统智能安全运维技术体系研究,有助于油气生产领域的安全建设,不仅为实现无故障油气生产系统提供技术支撑,也为世界油气行业智能化发展提供参考路径。

面向高强极薄铜箔制造过程的多维度质量控制系统设计

高强极薄铜箔的制造过程具有工艺复杂、各阶段耦合性强、产品质量影响因素多等特点,面向制造过程的质量控制技术及相关质量控制系统将是实现其高效稳定生产的重要保证。针对现阶段铜箔制造企业在高强极薄铜箔制造工艺稳定性和质量控制方面相关技术和软件系统上的缺失,提出了一套多维度质量控制系统设计方案。通过对铜箔制造过程及其质量管控需求进行分析,建立了具有三层架构的系统框架,重点从产品质量控制、工艺质量智能保证及生产系统运行质量监测3个维度对各子系统的内涵及功能进行了设计,为实现高强极薄铜箔的高效稳定及智能化生产提供保证,并可供质量控制领域自主工业软件研发借鉴。

基于BP神经网络的智能化刀具状态在线监测方法研究

在机床加工中,刀具的检测技术起着关键的功能。通过在刀具损坏以前及时监测并更换,造成的经济损失会大大减少,从而生产的效率和准确性得以大大提高。传统的刀具磨损监测方法需要手动提取冗长的特征,无法实现智能化监测。为了克服这一固有的局限性,进一步提高刀具磨损在线监测的准确度,本文使用了BP神经网络的刀具磨损在线监测方法,该种检测方法的主要好处在于减少了人工特征提取带来的复杂性和局限性。采用同类研究所用的材料集开展研究,证明了该技术在刀具磨损的检测上的有效性与可行性,在多种考核要求下的准确性比另外一些技术有了很大提升。

中国农工城固体废弃物全流程智慧管理研究进展

我国农业、工业和城市固体废弃物具有量大面广的特点,并表现出资源与污染的双重属性,亟需建立上述固废全生命周期的监管、处置和利用体系。鉴于此,固废全流程智慧管控策略应运而生并受到广泛关注。首先对全流程智慧管理进行概述,随后便依次对其在农业、工业和城市固废中的研究或应用现状进行了较为全面的梳理和评述。最后,从相关政策、主体和技术三个层面对固废全流程智慧管控策略的推广与优化提出了合理化建议,有望为固废精准监管与科学消纳,乃至乡村振兴、经济高质量发展和生态文明建设提供有价值的参考。

油气管道综合模拟实验系统的建设与实践

油气管道输送工况模拟实验系统是油气储运工程专业实验教学的重要组成部分,可助力学生对理论知识在工程实践中的应用形成直观认识。该实验系统在设计中以管道输送工艺为中心,形成综合性实验装置;建设中按照使用安全性、操作便捷性、实验直观性三方面要求展开空间布局,实现了就地控制与站场控制两级操控、功能分区、数据自动化采集等;应用中贯彻OBE理念,结合劳动教育、认知实习、专业课实验为本科教育提供全方位的实践平台,加深了学生对管输技术的理解,强化了学生的动手操作能力。