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The Interdisciplinary Research of Big Data and Wireless Channel: A Cluster-Nuclei Based Channel Model 被引量:27
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作者 Jianhua Zhang 《China Communications》 SCIE CSCD 2016年第S2期14-26,共13页
Recently,internet stimulates the explosive progress of knowledge discovery in big volume data resource,to dig the valuable and hidden rules by computing.Simultaneously,the wireless channel measurement data reveals big... Recently,internet stimulates the explosive progress of knowledge discovery in big volume data resource,to dig the valuable and hidden rules by computing.Simultaneously,the wireless channel measurement data reveals big volume feature,considering the massive antennas,huge bandwidth and versatile application scenarios.This article firstly presents a comprehensive survey of channel measurement and modeling research for mobile communication,especially for 5th Generation(5G) and beyond.Considering the big data research progress,then a cluster-nuclei based model is proposed,which takes advantages of both the stochastical model and deterministic model.The novel model has low complexity with the limited number of cluster-nuclei while the cluster-nuclei has the physical mapping to real propagation objects.Combining the channel properties variation principles with antenna size,frequency,mobility and scenario dug from the channel data,the proposed model can be expanded in versatile application to support future mobile research. 展开更多
关键词 channel model big data 5G massive MIMO machine learning CLUSTER
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Data Modeling and Data Analytics: A Survey from a Big Data Perspective 被引量:1
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作者 André Ribeiro Afonso Silva Alberto Rodrigues da Silva 《Journal of Software Engineering and Applications》 2015年第12期617-634,共18页
These last years we have been witnessing a tremendous growth in the volume and availability of data. This fact results primarily from the emergence of a multitude of sources (e.g. computers, mobile devices, sensors or... These last years we have been witnessing a tremendous growth in the volume and availability of data. This fact results primarily from the emergence of a multitude of sources (e.g. computers, mobile devices, sensors or social networks) that are continuously producing either structured, semi-structured or unstructured data. Database Management Systems and Data Warehouses are no longer the only technologies used to store and analyze datasets, namely due to the volume and complex structure of nowadays data that degrade their performance and scalability. Big Data is one of the recent challenges, since it implies new requirements in terms of data storage, processing and visualization. Despite that, analyzing properly Big Data can constitute great advantages because it allows discovering patterns and correlations in datasets. Users can use this processed information to gain deeper insights and to get business advantages. Thus, data modeling and data analytics are evolved in a way that we are able to process huge amounts of data without compromising performance and availability, but instead by “relaxing” the usual ACID properties. This paper provides a broad view and discussion of the current state of this subject with a particular focus on data modeling and data analytics, describing and clarifying the main differences between the three main approaches in what concerns these aspects, namely: operational databases, decision support databases and Big Data technologies. 展开更多
关键词 data modelING data ANALYTICS modelING LANGUAGE big data
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A New Efficient Obstacle Avoidance Control Method for Cars Based on Big Data and Just-in-Time Modeling 被引量:1
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作者 Tatsuya Kai 《Journal of Computer and Communications》 2018年第11期12-22,共11页
This paper provides a new obstacle avoidance control method for cars based on big data and just-in-time modeling. Just-in-time modeling is a new kind of data-driven control technique in the age of big data and is used... This paper provides a new obstacle avoidance control method for cars based on big data and just-in-time modeling. Just-in-time modeling is a new kind of data-driven control technique in the age of big data and is used in various real systems. The main property of the proposed method is that a gain and a control time which are parameters in the control input to avoid an encountered obstacle are computed from a database which includes a lot of driving data in various situations. Especially, the important advantage of the method is small computation time, and hence it realizes real-time obstacle avoidance control for cars. From some numerical simulations, it is showed that the new control method can make the car avoid various obstacles efficiently in comparison with the previous method. 展开更多
关键词 big data JUST-IN-TIME modelING CARS OBSTACLE AVOIDANCE Control
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Big Data in Chinese Government Governance: Analysis of Decision-Making Model Innovation and Practice
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作者 Peng Wang Bin Lu 《Journal of Computer and Communications》 2018年第12期129-142,共14页
The 19th National Congress of the Communist Party of China has put forward higher requirements for Chinese government governance. The government governance has developed to a higher stage. Meanwhile, it faces more cha... The 19th National Congress of the Communist Party of China has put forward higher requirements for Chinese government governance. The government governance has developed to a higher stage. Meanwhile, it faces more challenges, like lack of top-level design and information sharing. To develop a government governance decision-making innovation model, we should make good use of big data to mine in the grassroots government data management network. Both the characteristics of the times and the experience of the practice have proven that big data can empower government governance and promote the construction of a service-oriented government. 展开更多
关键词 big data GOVERNMENT GOVERNANCE model INNOVATION
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Foundation Study on Wireless Big Data: Concept, Mining, Learning and Practices 被引量:10
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作者 Jinkang Zhu Chen Gong +2 位作者 Sihai Zhang Ming Zhao Wuyang Zhou 《China Communications》 SCIE CSCD 2018年第12期1-15,共15页
Facing the development of future 5 G, the emerging technologies such as Internet of things, big data, cloud computing, and artificial intelligence is enhancing an explosive growth in data traffic. Radical changes in c... Facing the development of future 5 G, the emerging technologies such as Internet of things, big data, cloud computing, and artificial intelligence is enhancing an explosive growth in data traffic. Radical changes in communication theory and implement technologies, the wireless communications and wireless networks have entered a new era. Among them, wireless big data(WBD) has tremendous value, and artificial intelligence(AI) gives unthinkable possibilities. However, in the big data development and artificial intelligence application groups, the lack of a sound theoretical foundation and mathematical methods is regarded as a real challenge that needs to be solved. From the basic problem of wireless communication, the interrelationship of demand, environment and ability, this paper intends to investigate the concept and data model of WBD, the wireless data mining, the wireless knowledge and wireless knowledge learning(WKL), and typical practices examples, to facilitate and open up more opportunities of WBD research and developments. Such research is beneficial for creating new theoretical foundation and emerging technologies of future wireless communications. 展开更多
关键词 WIRELESS big data data model data MINING WIRELESS KNOWLEDGE KNOWLEDGE LEARNING future WIRELESS communications
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Layered Software Patterns for Data Analysis in Big Data Environment 被引量:3
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作者 Hossam Hakeem 《International Journal of Automation and computing》 EI CSCD 2017年第6期650-660,共11页
The proliferation of textual data in society currently is overwhelming, in particular, unstructured textual data is being constantly generated via call centre logs, emails, documents on the web, blogs, tweets, custome... The proliferation of textual data in society currently is overwhelming, in particular, unstructured textual data is being constantly generated via call centre logs, emails, documents on the web, blogs, tweets, customer comments, customer reviews, etc.While the amount of textual data is increasing rapidly, users ability to summarise, understand, and make sense of such data for making better business/living decisions remains challenging. This paper studies how to analyse textual data, based on layered software patterns, for extracting insightful user intelligence from a large collection of documents and for using such information to improve user operations and performance. 展开更多
关键词 big data data analysis patterns layered structure data modelling
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Use of community mobile phone big location data to recognize unusual patterns close to a pipeline which may indicate unauthorized activities and possible risk of damage 被引量:1
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作者 Shao-Hua Dong He-Wei Zhang +2 位作者 Lai-Bin Zhang Li-Jian Zhou Lei Guo 《Petroleum Science》 SCIE CAS CSCD 2017年第2期395-403,共9页
Damage caused by people and organizations unconnected with the pipeline management is a major risk faced by pipelines,and its consequences can have a huge impact.However,the present measures to monitor this have major... Damage caused by people and organizations unconnected with the pipeline management is a major risk faced by pipelines,and its consequences can have a huge impact.However,the present measures to monitor this have major problems such as time delays,overlooking threats,and false alarms.To overcome the disadvantages of these methods,analysis of big location data from mobile phone systems was applied to prevent third-party damage to pipelines,and a third-party damage prevention system was developed for pipelines including encryption mobile phone data,data preprocessing,and extraction of characteristic patterns.By applying this to natural gas pipelines,a large amount of location data was collected for data feature recognition and model analysis.Third-party illegal construction and occupation activities were discovered in a timely manner.This is important for preventing third-party damage to pipelines. 展开更多
关键词 PIPELINE big location data Third-party damage model Prevention
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Big Data for Organizations: A Review
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作者 Pwint Phyu Khine Wang Zhao Shun 《Journal of Computer and Communications》 2017年第3期40-48,共9页
Big data challenges current information technologies (IT landscape) while promising a more competitive and efficient contributions to business organizations. What big data can contribute to is what organizations have ... Big data challenges current information technologies (IT landscape) while promising a more competitive and efficient contributions to business organizations. What big data can contribute to is what organizations have been wanted for a long time ago. This paper presents the nature of big data and how organizations can advance their systems with big data technologies. By improving the efficiency and effectiveness of organizations, people can benefit the can take advantages of a more convenient life contributed by Information Technology. 展开更多
关键词 big data big data modelS ORGANIZATION INFORMATION System
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Geological Database for Plate Tectonic Reconstruction:A Conceptual Model
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作者 WANG Ping LIU Shaofeng 《Acta Geologica Sinica(English Edition)》 SCIE CAS CSCD 2019年第S01期66-69,共4页
We all live on one planet and geology has no borders.Countries that reside on different continents share the same architecture beneath the surface;they were once neighbors with common foundations.Interoperable geologi... We all live on one planet and geology has no borders.Countries that reside on different continents share the same architecture beneath the surface;they were once neighbors with common foundations.Interoperable geological data are now freely available to everyone for the benefit of society,demonstrating that geoscience can address both global and regional problems.Whilst increasingly large datasets("Big Data")provide clear opportunities(e.g.,Spina,2018). 展开更多
关键词 PLATE TECTONIC RECONSTRUCTION big data GML data model feature class
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Towards the Development of Best Data Security for Big Data
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作者 Yuan Tian 《Communications and Network》 2017年第4期291-301,共11页
Big data is becoming a well-known buzzword and in active use in many areas. Because of the velocity, variety, and volume of big data, security and privacy issues are magnified, which results in the traditional protect... Big data is becoming a well-known buzzword and in active use in many areas. Because of the velocity, variety, and volume of big data, security and privacy issues are magnified, which results in the traditional protection mechanisms for structured small scale data are inadequate for big data. Sensitivities around big data security and privacy are a hurdle that organizations need to overcome. In this paper, we review the current data security in big data and analysis its feasibilities and obstacles. Besides, we also introduced intelligent analytics to enhance security with the proposed security intelligence model. This research aims to summarize, organize and classify the information available in the literature to identify any gaps in current research and suggest areas for scholars and security researchers for further investigation. 展开更多
关键词 big data ANALYTICS SECURE big data Security INTELLIGENCE model
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HOW BIG DATA MAKES CONSTRUCTION PROJECT RISK INTACT
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作者 Daniel Ng 《办公自动化》 2014年第S1期394-400,共7页
Construction project is not a standalone engineering maneuver.It is closely linked to the well-being of local communities in concern.The city renovation in Beijing down center for Olympic 2008 transformed many antique... Construction project is not a standalone engineering maneuver.It is closely linked to the well-being of local communities in concern.The city renovation in Beijing down center for Olympic 2008 transformed many antique architecture and regional landscape.It gave a world-recognized achievement in China s modem development and manifested a major milestone in China's economic development.In the course of metro construction projects,there are substantial interwoven municipal structures influencing the success of the projects,which including,but the least,all underground cables and ducts,sewage system,the power consumption of construction works,traffic diversion,air pollution,expatriate business activities and social security.There are many US and UK project insurance companies moving into Asia Pacific.They are doing re-insurance business on major construction guarantee,such as machinery damage,project on-time,power consumption,claims from contractors and communities.Environmental information,such as water quality,indoor and outdoor air quality,people inflow and lift waiting time play deterministic roles in construction's fit-touse.Big Data is a contemporary buzzword since 2013,and the key competence is to provide real time response to heuristic syndrome in order to make short-term prediction.This paper attempts to develop a conceptual model in big data for construction 展开更多
关键词 Construction PROJECT RISK big data GRAPH modelling
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A brief procedure for big data analysis of gene expression 被引量:1
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作者 Kewei Wang Wenji Wang Mang Li 《Animal Models and Experimental Medicine》 2018年第3期189-193,共5页
There are a lot of biological and experimental data from genomics, proteomics, drug screening, medicinal chemistry, etc. A large amount of data must be analyzed by special methods of statistics, bioinformatics, and co... There are a lot of biological and experimental data from genomics, proteomics, drug screening, medicinal chemistry, etc. A large amount of data must be analyzed by special methods of statistics, bioinformatics, and computer science. Big data analysis is an effective way to build scientific hypothesis and explore internal mechanism.Here, gene expression is taken as an example to illustrate the basic procedure of the big data analysis. 展开更多
关键词 big data ANALYSIS CLUSTER ANALYSIS MICROARRAY PCA ANALYSIS regression model
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Advance Techniques in Medical Imaging under Big Data Analysis: Covid-19 Images
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作者 S. Zimeras 《Advances in Computed Tomography》 2021年第1期1-10,共10页
Quantitative analysis of digital images requires detection and segmentation of the borders of the object of interest. Accurate segmentation is required for volume determination, 3D rendering, radiation therapy, and su... Quantitative analysis of digital images requires detection and segmentation of the borders of the object of interest. Accurate segmentation is required for volume determination, 3D rendering, radiation therapy, and surgery planning. In medical images, segmentation has traditionally been done by human experts. Substantial computational and storage requirements become especially acute when object orientation and scale have to be considered. Therefore, automated or semi-automated segmentation techniques are essential if these software applications are ever to gain widespread clinical use. Many methods have been proposed to detect and segment 2D shapes, most of which involve template matching. Advanced segmentation techniques called Snakes or active contours have been used, considering deformable models or templates. The main purpose of this work is to apply segmentation techniques for the definition of 3D organs (anatomical structures) when big data information has been stored and must be organized by the doctors for medical diagnosis. The processes would be implemented in the CT images from patients with COVID-19. 展开更多
关键词 Segmentation Techniques big data Analysis Contour model Shape model Radial Basis Function Active Contours Snakes
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A Surfing Concurrence Transaction Model for Key-Value NoSQL Databases
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作者 Changqing Li Jianhua Gu 《Journal of Software Engineering and Applications》 2018年第10期467-485,共19页
As more and more application systems related to big data were developed, NoSQL (Not Only SQL) database systems are becoming more and more popular. In order to add transaction features for some NoSQL database systems, ... As more and more application systems related to big data were developed, NoSQL (Not Only SQL) database systems are becoming more and more popular. In order to add transaction features for some NoSQL database systems, many scholars have tried different techniques. Unfortunately, there is a lack of research on Redis’s transaction in the existing literatures. This paper proposes a transaction model for key-value NoSQL databases including Redis to make possible allowing users to access data in the ACID (Atomicity, Consistency, Isolation and Durability) way, and this model is vividly called the surfing concurrence transaction model. The architecture, important features and implementation principle are described in detail. The key algorithms also were given in the form of pseudo program code, and the performance also was evaluated. With the proposed model, the transactions of Key-Value NoSQL databases can be performed in a lock free and MVCC (Multi-Version Concurrency Control) free manner. This is the result of further research on the related topic, which fills the gap ignored by relevant scholars in this field to make a little contribution to the further development of NoSQL technology. 展开更多
关键词 NOSQL big data SURFING CONCURRENCE TRANSACTION model KEY-VALUE NOSQL databases REDIS
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大数据背景下研究性教学模式的探究与实践——以“食品营养学”为例
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作者 李宁 李天歌 +4 位作者 宋莲军 高晓平 李倩 乔明武 黄现青 《农产品加工》 2026年第1期135-138,共4页
探讨了大数据背景下研究性教学模式在“食品营养学”课程中的应用与实践。首先,分析了传统教学模式存在的问题,如教学理念落后、教学资源配置不足等。随后,介绍了大数据技术在教育领域的广泛应用及其对营养健康领域带来的变革,为研究性... 探讨了大数据背景下研究性教学模式在“食品营养学”课程中的应用与实践。首先,分析了传统教学模式存在的问题,如教学理念落后、教学资源配置不足等。随后,介绍了大数据技术在教育领域的广泛应用及其对营养健康领域带来的变革,为研究性教学模式的引入提供了背景支持。在“食品营养学”课程中,通过采用研究性教学模式,激发学生的学习兴趣,培养其主动学习和综合分析能力。具体实施方式包括确定研究性学习问题、学生分组选题、查阅资料、学习讨论、信息梳理、分析简答问题、撰写论文及制作PPT进行答辩等。同时,借助大数据技术,实现了对学生学习过程的精准跟踪和反馈,优化了教学效果。最后,总结了研究性教学模式在“食品营养学”课程中的实践成果,包括学生创新能力的提升、学习成绩的提高及教师教学能力的增强等。 展开更多
关键词 大数据 研究性教学 教学模式 食品营养学
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基于元胞自动机模型的松材线虫病小班尺度预测
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作者 周宏威 李永正 +5 位作者 郭文辉 陈怡帆 胡浩昌 张思岩 崔迪 陈雨茉 《林业科学》 北大核心 2026年第1期133-143,共11页
【目的】为探究影响松材线虫病传播扩散的主要影响因素,结合自然气候、人类活动以及地理空间特征多源数据,围绕松材线虫病“传入-定殖-扩散”的生态入侵过程,构建适用于更小空间尺度数据的传播预测模型,实现对松材线虫病高风险发生地区... 【目的】为探究影响松材线虫病传播扩散的主要影响因素,结合自然气候、人类活动以及地理空间特征多源数据,围绕松材线虫病“传入-定殖-扩散”的生态入侵过程,构建适用于更小空间尺度数据的传播预测模型,实现对松材线虫病高风险发生地区的精准预测和早期预警。【方法】基于国家林业和草原局公布的江苏省松材线虫病小班本底发生数据,结合松材线虫病的生态特性和地理空间分布规律,选取包含自然气候、人类活动因素以及空间特征等25项影响因子数据,采用主成分分析方法进行数据预处理,通过Spearman相关性分析方法和Apriori数据挖掘算法,探究各影响因子与松材线虫病发生之间的相互作用关系。结合贝叶斯估计方法对影响因子数据进行特征增强,建立灰狼优化算法-元胞自动机模型模拟松材线虫病的传播扩散过程,同时与其他5种主流机器学习模型预测结果进行横向对比验证,通过计算其精确率、召回率和AUC等评价指标对模型性能进行验证。【结果】构建的灰狼优化算法-元胞自动机模型在松材线虫病新发小班预测中表现出优异的性能,模型召回率达到78.5%,显著优于其他5种主流机器学习模型;同时,其AUC值达到89.0%,表明模型在识别新发疫情点位的同时,兼顾较高的整体预测准确性与判别能力。本研究进一步证实地理空间特征在松材线虫病传播预测中的重要性,并验证元胞自动机模型在处理复杂时空数据和更精细尺度空间数据预测方面的高度适用性。【结论】木材运输是驱动松材线虫病传播扩散的关键因素,而温度与降水的差异也在显著程度上影响其发生风险。作为一种融合空间异质性与时间动态特征的建模方法,元胞自动机模型在处理复杂生态数据与入侵物种风险评估方面展现出较高的适用性与灵活性,可为松材线虫病的精准防控与高效管理提供有力的技术支撑。 展开更多
关键词 松材线虫病 传播预测模型 大数据 数据挖掘 元胞自动机
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大数据分析在公路预防性养护行业中的应用研究
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作者 王华 《科技创新与生产力》 2026年第1期38-40,共3页
在公路预防性养护中应用大数据分析,通过数据处理和分析技术提高公路养护工作的效率、准确性和科学性。首先对公路预防性养护进行了概述,其次对大数据分析在公路预防性养护中的应用价值进行了分析,最后提出了大数据分析在公路预防性养... 在公路预防性养护中应用大数据分析,通过数据处理和分析技术提高公路养护工作的效率、准确性和科学性。首先对公路预防性养护进行了概述,其次对大数据分析在公路预防性养护中的应用价值进行了分析,最后提出了大数据分析在公路预防性养护行业中的应用策略,希望为公路的科学、智慧养护提供参考价值。 展开更多
关键词 大数据分析 公路养护 模型 应用
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卫生资源优化的大数据分析方法
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作者 陈晶 《计算机应用文摘》 2026年第2期177-179,共3页
文章探讨了大数据分析在卫生资源优化中的应用方法与框架。针对卫生资源配置中存在的区域不均衡、结构性矛盾及利用效率偏低等问题,构建了一个整合多源数据、融合预测模型与优化算法的综合分析模型。通过引入数据治理机制保障数据安全... 文章探讨了大数据分析在卫生资源优化中的应用方法与框架。针对卫生资源配置中存在的区域不均衡、结构性矛盾及利用效率偏低等问题,构建了一个整合多源数据、融合预测模型与优化算法的综合分析模型。通过引入数据治理机制保障数据安全与质量,并采用集成学习等先进预测技术提升卫生资源需求预判的精准性,该模型能够支持实现动态、精准的资源调配与布局优化。研究表明,基于大数据的资源优化策略可显著提升资源配置的公平性、动态适应性与整体使用效率,为公共卫生体系在常态与应急状态下的资源管理提供系统化的决策支持。 展开更多
关键词 大数据分析 卫生资源 优化模型 资源配置 数据挖掘
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生成式人工智能赋能职业教育大模型建设:功能逻辑与路径策略
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作者 谢青松 白然 郭冬梅 《职业技术教育》 北大核心 2026年第1期59-66,共8页
生成式人工智能的全球兴起与应用推动着职业教育体系和职业技能人才培养结构的深层变革。生成式人工智能的强大数据分析与处理能力对职业教育专业设置和就业面向岗位产生直接影响,驱动职业教育核心要素重组与生态演进,重塑职业教育技能... 生成式人工智能的全球兴起与应用推动着职业教育体系和职业技能人才培养结构的深层变革。生成式人工智能的强大数据分析与处理能力对职业教育专业设置和就业面向岗位产生直接影响,驱动职业教育核心要素重组与生态演进,重塑职业教育技能人才培养范式。基于设计研究范式,构建职业教育大模型的路径框架,具体包括需求对齐、数据工程、模型选型、场景微调、落地闭环等五个步骤。职业教育大模型的具体建设策略是:加强顶层设计与政策规划,优化资源整合与共享;聚焦数据治理与成效监测,立足服务师生教学与实践;重视全面推广与具体落地实施,保持持续优化与改进。 展开更多
关键词 生成式人工智能 职业教育 大模型 教育强国 大数据
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基于区域医疗大数据的居民健康分级评价模型的构建与验证
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作者 朱文迪 陈华 +3 位作者 王亚琳 段熠 孙玉梅 孙宏玉 《军事护理》 北大核心 2026年第1期10-14,共5页
目的构建科学、可操作的居民健康评价指标体系及分级评价模型。方法通过专家函询构建居民健康评价指标体系并采用层次分析法确定指标权重,进而以评价体系的健康指标值为输入、健康分级为输出,采用反向传播神经网络算法建立居民健康分级... 目的构建科学、可操作的居民健康评价指标体系及分级评价模型。方法通过专家函询构建居民健康评价指标体系并采用层次分析法确定指标权重,进而以评价体系的健康指标值为输入、健康分级为输出,采用反向传播神经网络算法建立居民健康分级评价模型并验证。结果2轮函询专家积极程度均为100.00%,专家权威系数均为0.89,条目重要性评分均值分别为3.90~5.00、4.00~5.00,变异系数分别为0.00~0.34、0.00~0.28,肯德尔协调系数分别为0.202、0.289,最终形成的指标体系由5个一级指标、14个二级指标、25个三级指标构成;居民健康分级评价模型在训练集和验证集的总体准确率为98.54%和91.63%,验证集模型曲线下面积分别为0.995、0.975、0.965、0.982、0.998。结论本研究构建的指标体系涵盖居民健康的关键影响要素,健康分级评价模型具有良好区分度,可实现对居民健康状况的客观量化评价。 展开更多
关键词 健康状况 大数据 神经网络模型
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