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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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基于云边协同的大数据模型高效部署研究
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作者 刘顺 陈良英 《科技资讯》 2026年第5期62-65,共4页
随着大数据与人工智能技术的快速发展,大数据模型在各领域的应用日益广泛,但模型部署面临诸多挑战,如传统云计算模式的高延迟、高带宽成本、边缘计算模式下资源受限等问题。云边协同技术为解决这些问题提供了新的思路。本文深入研究基... 随着大数据与人工智能技术的快速发展,大数据模型在各领域的应用日益广泛,但模型部署面临诸多挑战,如传统云计算模式的高延迟、高带宽成本、边缘计算模式下资源受限等问题。云边协同技术为解决这些问题提供了新的思路。本文深入研究基于云边协同的大数据模型高效部署方案,通过构建云边协同架构、设计轻量化模型压缩算法、优化资源调度策略等,有效提升大数据模型的部署效率、降低成本,为相关领域的发展提供有力支持。 展开更多
关键词 云边协同 大数据模型 高效部署 模型压缩 资源调度
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数智化医疗健康管理研究综述与前沿展望
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作者 周文慧 李梦雨 +1 位作者 吴邦安 党媛媛 《系统工程》 北大核心 2026年第1期1-18,共18页
随着人工智能、大数据等数字技术的快速发展,医疗健康管理正经历从传统模式向数智化范式的深刻转变。本文通过对394篇相关文献的分析,系统性界定“数智化医疗健康管理”的概念内涵与研究边界,构建四个核心方向的分析框架:智能诊疗与辅... 随着人工智能、大数据等数字技术的快速发展,医疗健康管理正经历从传统模式向数智化范式的深刻转变。本文通过对394篇相关文献的分析,系统性界定“数智化医疗健康管理”的概念内涵与研究边界,构建四个核心方向的分析框架:智能诊疗与辅助决策技术、医疗健康大数据管理与安全、数智化医疗服务模式创新、智能监测与健康预防。研究发现,该领域整体呈现从技术验证向理论建构、从分散研究向系统整合的发展态势。基于现状分析,本文提出未来研究的重点方向和发展趋势,包括算法可解释性、人机协同机制、跨机构数据协作、个性化健康干预、决策复杂性与伦理治理等关键问题,为推动数智化医疗健康管理的理论发展和实践应用提供参考。 展开更多
关键词 数智化 医疗健康管理 智能诊疗 医疗健康大数据 服务模式创新 智能监测 健康预防
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GoldMiner-AI:大数据与人工智能找矿系统的设计与实现
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作者 周永章 朱彪彪 +9 位作者 童小畅 李丹 张彤 牛露佳 于新慧 张玙情 王郑哲 郭亦嘉 李文佳 张灿 《地学前缘》 北大核心 2026年第4期1-11,共11页
针对当前地质找矿智能化转型中“从数据接入到智能分析的全流程自动化”以及“贯穿数据获取、融合处理、异常识别与智能预测的全流程端到端系统”仍属关键瓶颈的现实挑战,本文介绍笔者近年来围绕构建大数据与人工智能找矿新范式所持续... 针对当前地质找矿智能化转型中“从数据接入到智能分析的全流程自动化”以及“贯穿数据获取、融合处理、异常识别与智能预测的全流程端到端系统”仍属关键瓶颈的现实挑战,本文介绍笔者近年来围绕构建大数据与人工智能找矿新范式所持续性开展的研究成果,重点阐述面向找矿任务的全流程智能系统——GoldMiner-AI的构建与应用。该平台基于RuoYi-Cloud-Plus微服务架构,采用PostGIS、Neo4j、Milvus与MySQL协同的多数据库体系,实现对地质、地球化学、地球物理、钻孔、野外观察及文本报告等多源异构地学数据的统一管理。在智能化核心模块方面,系统集成了KAR-Graph异常识别框架与MAF-Net多源特征融合深度学习模型,并结合知识图谱与检索增强生成技术,构建了面向找矿垂直领域的大语言模型,形成了从异常识别、靶区圈定、知识推理到智能问答的完整智能工作流。在右江盆地、钦杭成矿带南段等矿区的验证结果表明:(1)系统能够有效识别卡林型金矿的Au-As-Sb-Hg异常组合,并深入挖掘与矿床成因相关的地球化学指纹;(2)通过多源图层叠加分析,系统可准确预测铅锌矿化带的空间位置;(3)垂直领域大语言模型能够显著减轻通用模型的“幻觉”现象,提升地学知识问答的准确性。GoldMiner-AI为矿产预测提供了一个可复现、可扩展、可工程化部署的系统平台,推动了找矿工作向全面智能化方向发展。 展开更多
关键词 智能找矿 大数据挖掘 大语言模型 深度学习 检索增强生成 知识图谱
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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 被引量:1
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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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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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