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基于大数据和云计算技术的数字化课程资源平台
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作者 罗海辉 《信息与电脑》 2023年第23期251-253,共3页
为提高课程资源平台的承载能力,本文通过引进大数据技术与云计算技术,开展数字化课程资源平台的设计研究。为了避免课程资源在流通中由于存储异常出现失真等问题,进行平台中云存储服务器的选型。在此基础上,利用大数据技术,对数据进行... 为提高课程资源平台的承载能力,本文通过引进大数据技术与云计算技术,开展数字化课程资源平台的设计研究。为了避免课程资源在流通中由于存储异常出现失真等问题,进行平台中云存储服务器的选型。在此基础上,利用大数据技术,对数据进行实时采集、分类、存储和分析,提取其中有价值的信息,将其作为课程资源的关键属性,进行课程资源属性的集约处理;在平台预处理终端录入数字化课程资源类别划分标准与依据,进行数字化课程资源类别划分、共享与个性化推荐。实验结果表明:该平台的负载能力较强,其后台运行带宽不会随着在线人数的增加而出现下降或异常中断现象。 展开更多
关键词 大数据 属性集约 平台设计 课程资源 数字化 云计算技术
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MAINTENANCE LEVEL DECISION OF AERO-ENGINE BASED ON VPRS THEORY 被引量:3
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作者 张海军 左洪福 梁剑 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI 2005年第4期281-284,共4页
An aero-engine is a typically repairable and complex system and its maintenance level has a close relationship with the maintenance cost. The inaccurate measurement for the maintenance level of an aero-engine can indu... An aero-engine is a typically repairable and complex system and its maintenance level has a close relationship with the maintenance cost. The inaccurate measurement for the maintenance level of an aero-engine can induce higher overhaul maintenance costs. Variable precision rough set (VPRS) theory is used to determine the maintenance level of an aero-engine. According to the relationship between condition information and performance parameters of aero-engine modules, decision rules are established for reflecting the real condition of an aeroengine when its maintenance level needs to be determined. Finally, the CF6 engine is used as an example to illustrate the method to be effective. 展开更多
关键词 repairable system AERO-ENGINE maintenance level variable precision rough set attribute reduction
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Co-evolutionary cloud-based attribute ensemble multi-agent reduction algorithm
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作者 丁卫平 王建东 +1 位作者 张晓峰 管致锦 《Journal of Southeast University(English Edition)》 EI CAS 2016年第4期432-438,共7页
In order to improve the performance of the attribute reduction algorithm to deal with the noisy and uncertain large data, a novel co-evolutionary cloud-based attribute ensemble multi-agent reduction(CCAEMR) algorith... In order to improve the performance of the attribute reduction algorithm to deal with the noisy and uncertain large data, a novel co-evolutionary cloud-based attribute ensemble multi-agent reduction(CCAEMR) algorithm is proposed.First, a co-evolutionary cloud framework is designed under the M apReduce mechanism to divide the entire population into different co-evolutionary subpopulations with a self-adaptive scale. Meanwhile, these subpopulations will share their rewards to accelerate attribute reduction implementation.Secondly, a multi-agent ensemble strategy of co-evolutionary elitist optimization is constructed to ensure that subpopulations can exploit any correlation and interdependency between interacting attribute subsets with reinforcing noise tolerance.Hence, these agents are kept within the stable elitist region to achieve the optimal profit. The experimental results show that the proposed CCAEMR algorithm has better efficiency and feasibility to solve large-scale and uncertain dataset problems with complex noise. 展开更多
关键词 co-evolutionary elitist optimization attribute reduction co-evolutionary cloud framework multi-agent ensemble strategy neonatal brain 3D-MRI
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An improved reduction algorithm based on the degree of attribute discernibility 被引量:1
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作者 张铮 Yu Daoyuan Li Peigen 《High Technology Letters》 EI CAS 2007年第3期244-248,共5页
This paper deals with the problem of attribute discernibility reduction and proposes some new concepts to rough set theory (RST) based on the discernibility matrix of Skowron, such as secondary core, regeneration ma... This paper deals with the problem of attribute discernibility reduction and proposes some new concepts to rough set theory (RST) based on the discernibility matrix of Skowron, such as secondary core, regeneration matrix and the degree of attribute discernibility (DAD). This paper puts forward an attribute reduction algorithm based on maximum discernibility degree, which opens up an effective way of gaining minimum attribute reduction of decision table. The efficacy of this algorithm has been verified by practical application in a diagnostic system of loader, which substantially decreases information gathering requirement and lowers the overall cost with no loss of accuracy. 展开更多
关键词 attribute reduction discernibility matrix degree of attribute discernibility (DAD) secondary core regeneration discernibility matrix
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