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An Efficient Stacked-LSTM Based User Clustering for 5G NOMA Systems 被引量:1
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作者 S.Prabha Kumaresan Chee Keong Tan Yin Hoe Ng 《Computers, Materials & Continua》 SCIE EI 2022年第9期6119-6140,共22页
Non-orthogonal multiple access(NOMA)has been a key enabling technology for the fifth generation(5G)cellular networks.Based on the NOMA principle,a traditional neural network has been implemented for user clustering(UC... Non-orthogonal multiple access(NOMA)has been a key enabling technology for the fifth generation(5G)cellular networks.Based on the NOMA principle,a traditional neural network has been implemented for user clustering(UC)to maximize the NOMA system’s throughput performance by considering that each sample is independent of the prior and the subsequent ones.Consequently,the prediction of UC for the future ones is based on the current clustering information,which is never used again due to the lack of memory of the network.Therefore,to relate the input features of NOMA users and capture the dependency in the clustering information,time-series methods can assist us in gaining a helpful insight into the future.Despite its mathematical complexity,the essence of time series comes down to examining past behavior and extending that information into the future.Hence,in this paper,we propose a novel and effective stacked long short term memory(S-LSTM)to predict the UC formation of NOMA users to enhance the throughput performance of the 5G-based NOMA systems.In the proposed strategy,the S-LSTM is modelled to handle the time-series input data to improve the predicting accuracy of UC of the NOMA users by implementing multiple LSTM layers with hidden cells.The implemented LSTM layers have feedback connections that help to capture the dependency in the clustering information as it propagates between the layers.Specifically,we develop,train,validate and test the proposed model to predict the UC formation for the futures ones by capturing the dependency in the clustering information based on the time-series data.Simulation results demonstrate that the proposed scheme effectively predicts UC and thereby attaining near-optimal throughput performance of 98.94%compared to the exhaustive search method. 展开更多
关键词 Non-orthogonal multiple access(NOMA) deep neural network(DNN) long short term memory(LSTM) temporal channel user clustering
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Maximum throughput design of wireless powered communication network with IRS-NOMA based on user clustering 被引量:1
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作者 Guo Hui Zhao Xuehui 《The Journal of China Universities of Posts and Telecommunications》 EI CSCD 2023年第3期55-64,共10页
A wireless powered communication network(WPCN)assisted by intelligent reflecting surface(IRS)is proposed in this paper,which can transfer information by non-orthogonal multiple access(NOMA)technology.In the system,in ... A wireless powered communication network(WPCN)assisted by intelligent reflecting surface(IRS)is proposed in this paper,which can transfer information by non-orthogonal multiple access(NOMA)technology.In the system,in order to ensure that the hybrid access point(H-AP)can correctly decode user information via successive interference cancellation(SIC)technology,the information transmit power of user needs to satisfy a certain threshold,so as to meet the corresponding SIC constraints.Therefore,when the number of users who transfer information simultaneously increases,the system performance will be greatly restricted.To minimize the influence of SIC constraints on system performance,users are firstly clustered,and then each cluster collects energy from H-AP and finally,users transfer information based on NOMA with the assistance of IRS.Specifically,this paper aims to maximize the sum throughput of the system by jointly optimizing the beamforming of IRS and resource allocation of the system.The semi-definite relaxation(SDR)algorithm is employed to alternately optimize the beamforming of IRS in each time slot,and the joint optimization problem about user’s transmit power and time is transformed into two optimal time allocation sub-problems.The numerical results show that the proposed optimization scheme can effectively improve the sum throughput of the system.In addition,the results in the paper further reveals the positive impact of IRS on improving the sum throughput of the system. 展开更多
关键词 wireless powered communication network(WPCN) intelligent reflecting surface(IRS) user clustering
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Analysis of users’ electricity consumption behavior based on ensemble clustering 被引量:7
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作者 Qi Zhao Haolin Li +2 位作者 Xinying Wang Tianjiao Pu Jiye Wang 《Global Energy Interconnection》 2019年第6期479-489,共11页
Due to the increase in the number of smart meter devices,a power grid generates a large amount of data.Analyzing the data can help in understanding the users’electricity consumption behavior and demands;thus,enabling... Due to the increase in the number of smart meter devices,a power grid generates a large amount of data.Analyzing the data can help in understanding the users’electricity consumption behavior and demands;thus,enabling better service to be provided to them.Performing power load profile clustering is the basis for mining the users’electricity consumption behavior.By examining the complexity,randomness,and uncertainty of the users’electricity consumption behavior,this paper proposes an ensemble clustering method to analyze this behavior.First,principle component analysis(PCA)is used to reduce the dimensions of the data.Subsequently,the single clustering method is used,and the majority is selected for integrated clustering.As a result,the users’electricity consumption behavior is classified into different modes,and their characteristics are analyzed in detail.This paper examines the electricity power data of 19 real users in China for simulation purposes.This manuscript provides a thorough analysis along with suggestions for the users’weekly electricity consumption behavior.The results verify the effectiveness of the proposed method. 展开更多
关键词 users’electricity consumption Ensemble clustering Dimensionality reduction cluster validity
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User Model Clustering
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作者 Loc Nguyen 《Journal of Data Analysis and Information Processing》 2014年第2期41-48,共8页
User model which is the representation of information about user is the heart of adaptive systems. It helps adaptive systems to perform adaptation tasks. There are two kinds of adaptations: 1) Individual adaptation re... User model which is the representation of information about user is the heart of adaptive systems. It helps adaptive systems to perform adaptation tasks. There are two kinds of adaptations: 1) Individual adaptation regarding to each user;2) Group adaptation focusing on group of users. To support group adaptation, the basic problem which needs to be solved is how to create user groups. This relates to clustering techniques so as to cluster user models because a group is considered as a cluster of similar user models. In this paper we discuss two clustering algorithms: k-means and k-medoids and also propose dissimilarity measures and similarity measures which are applied into different structures (forms) of user models like vector, overlay, and Bayesian network. 展开更多
关键词 user MODEL cluster
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А Novel AP Placement Algorithm Based on User Distribution for Indoor WLAN System 被引量:3
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作者 ShuTang Lin Ma Yubin Xu 《China Communications》 SCIE CSCD 2016年第10期108-118,共11页
AP deployment is significant for indoor WLAN system to achieve seamless coverage. The available algorithms do not take user distribution into consideration so that poor user coverage and imbalanced network load occur.... AP deployment is significant for indoor WLAN system to achieve seamless coverage. The available algorithms do not take user distribution into consideration so that poor user coverage and imbalanced network load occur. Therefore, this paper proposed a novel AP placement algorithm to bridge the AP deployment with user distribution. The proposed algorithm employs statistics theory to model the user distribution as its location and probability. Then we obtain the AP location based on the fuzzy C-clustering algorithm. The proposed algorithm is practical for implementation, which means the actual signal transmission isn't required in our proposed method. The simulation results show that the proposed algorithm could automatically achieve a good AP deployment with different user distribution, and provide a good performance in the maximum users and AP load balance in WLAN. 展开更多
关键词 AP placement user distribution fuzzy C-clustering artificial fish maximum users AP load balance
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下行RIS-NOMA的用户集群方法 被引量:1
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作者 彭艺 吴桐 杨青青 《中山大学学报(自然科学版)(中英文)》 CAS CSCD 北大核心 2024年第1期128-136,共9页
为提高用户分布非均匀的场景下可重构智能表面(RIS)辅助下行非正交多址(NOMA)通信系统的性能,提出了一种分布式RIS辅助下行NOMA的用户聚类方案。首先,采用自适应几何分布(AGD)聚类算法划分用户集群(UCs),从而为各UC匹配RIS。然后,利用... 为提高用户分布非均匀的场景下可重构智能表面(RIS)辅助下行非正交多址(NOMA)通信系统的性能,提出了一种分布式RIS辅助下行NOMA的用户聚类方案。首先,采用自适应几何分布(AGD)聚类算法划分用户集群(UCs),从而为各UC匹配RIS。然后,利用分式规划(FP)方法将非凸最大化频谱效率问题转换为凸优化问题。最后,为UC内用户逐级进行功率分配(PA)与被动波束形成(PB)。仿真结果表明,与谱聚类(SPC)、K均值(K-means)、高斯混合模型(GMM)聚类方案和正交多址(OMA)方案相比,在AGD方案下,功率对频谱效率提升了7%、14%、19%和42%的增益,反射面对频谱效率提升了16%、19%、26%和40%的增益。 展开更多
关键词 可重构智能表面 非正交多址 用户集群 分式规划
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Characteristics Classification of Mobile Apps on Apple Store Using Clustering
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作者 Boxi Fu 《Journal of Data Analysis and Information Processing》 2020年第2期69-85,共17页
This research is interested in the user ratings of Apps on Apple Stores. The purpose of this research is to have a better understanding of some characteristics of the good Apps on Apple Store so Apps makers can potent... This research is interested in the user ratings of Apps on Apple Stores. The purpose of this research is to have a better understanding of some characteristics of the good Apps on Apple Store so Apps makers can potentially focus on these traits to maximize their profit. The data for this research is collected from kaggle.com, and originally collected from iTunes Search API, according to the abstract of the data. Four different attributes contribute directly toward an App’s user rating: rating_count_tot, rating_count_ver, user_rating and user_rating_ver. The relationship between Apps receiving higher ratings and Apps receiving lower ratings is analyzed using Exploratory Data Analysis and Data Science technique “clustering” on their numerical attributes. Apps, which are represented as a data point, with similar characteristics in rating are classified as belonging to the same cluster, while common characteristics of all Apps in the same clusters are the determining traits of Apps for that cluster. Both techniques are achieved using Google Colab and libraries including pandas, numpy, seaborn, and matplotlib. The data reveals direct correlation from number of devices supported and languages supported to user rating and inverse correlation from size and price of the App to user rating. In conclusion, free small Apps that many different types of users are able to use are generally well rated by most users, according to the data. 展开更多
关键词 MOBILE APPS clusterING user Rating Pairplot SCATTER PLOT FUNCTIONALITY
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Approach to MAI cancellation for micro-satellite clusters
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作者 HUANG Jiajun ZHANG Chaojie JIN Xiaojun 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2019年第5期823-830,共8页
With the development of micro-satellite technology,traditional monolithic satellites can be replaced by micro-satellite clusters to achieve high flexibility and dynamic reconfiguration capability.For satellite cluster... With the development of micro-satellite technology,traditional monolithic satellites can be replaced by micro-satellite clusters to achieve high flexibility and dynamic reconfiguration capability.For satellite clusters based on the frequency division-code division multiple access(FD-CDMA)communication system,the inter-satellite ranging precision is usually constrained due to the influence ofmulti-address interference(MAI).Themulti-user detection(MUD)is a solution to MAI,which can be divided into two categories:the linear detector(LD)and the non-linear detector(NLD).The general idea of the LD is aiming to make a better decision during the symbol decision process by using the information of all channels.However,it is not beneficial for the signal phase tracking precision.Instead,the principle of the NLD is to rebuild the interference signal and cancel it from the original one,which can improve the ranging performance at the expense of considerable delays.In order to enable simultaneous ranging and communication and reduce multi-node ranging performance degradation,this paper proposes an NLD scheme based on a delay locked loop(DLL),which simplifies the receiver structure and introduces no delay in the decision process.This scheme utilizes the information obtained from the interference channel to reconstruct the interference signal and then cancels it from the original delayed signal.Therefore,the DLL input signal-to-interference ratio(SIR)of the desired channel can be significantly improved.The experimental results show that with the proposed scheme,the standard deviation of the tracking steady error is decreased from 5.59 cm to 3.97 cm for SIR=5 dB,and 13.53 cm to 5.77 cm for SIR=-5 dB,respectively. 展开更多
关键词 MICRO-SATELLITE SATELLITE clusterS multi-user detection(MUD) interference CANCELLATION inter-satellite ranging
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Blind localization of multiple primary users without number knowledge
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作者 邢志强 宁士勇 +1 位作者 李炜 宋鹏 《Journal of Harbin Institute of Technology(New Series)》 EI CAS 2012年第5期113-117,共5页
A novel multiple PUs (Primary Users) localization algorithm was proposed, which estimates the number of PUs by SVD (Singular Value Decomposition) method and seeks non-cooperative PUs' position by executing k-mean ... A novel multiple PUs (Primary Users) localization algorithm was proposed, which estimates the number of PUs by SVD (Singular Value Decomposition) method and seeks non-cooperative PUs' position by executing k-mean clustering and iterative operations. The simulation results show that the proposed method can determined the number of PUs blindly and achieves better performance than traditional expectation-maximization (EM) algorithm. 展开更多
关键词 multiple primary user LOCALIZATION SVD ITERATIVE k-mean clustering
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基于多特征符号聚合近似和层次聚类的户变关系识别方法 被引量:1
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作者 周赣 茅欢 +2 位作者 冯燕钧 华济民 曾瑛 《电力系统自动化》 EI CSCD 北大核心 2024年第3期133-141,共9页
针对低压配电台区拓扑档案中可能存在的户变关系异常问题,文中提出了一种基于多特征符号聚合近似(MF-SAX)和层次聚类的户变关系识别方法。首先,运用符号聚合近似表达方法将用户电压时间序列转化为字符串序列,并引入电压波动系数和电压... 针对低压配电台区拓扑档案中可能存在的户变关系异常问题,文中提出了一种基于多特征符号聚合近似(MF-SAX)和层次聚类的户变关系识别方法。首先,运用符号聚合近似表达方法将用户电压时间序列转化为字符串序列,并引入电压波动系数和电压变化趋势两个附加参数对其特征表达进行强化。然后,基于编辑距离生成用户电压曲线相似性矩阵,并结合层次聚类算法实现户变关系的识别。最后,实际算例结果表明,提出的方法相比于现有方法准确率更高,误报更少,能直接应对数据缺失的情况,且具有更高的效率。 展开更多
关键词 低压配电台区 户变关系 层次聚类 拓扑识别 电压曲线相似性
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Learning Hierarchical User Interest Models from Web Pages
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作者 YANG Feng-qin SUN Tie-li SUN Ji-gui 《Wuhan University Journal of Natural Sciences》 EI CAS 2006年第1期6-10,共5页
We propose an algorithm for learning hierarchical user interest models according to the Web pages users have browsed. In this algorithm, the interests of a user are represented into a tree which is called a user inter... We propose an algorithm for learning hierarchical user interest models according to the Web pages users have browsed. In this algorithm, the interests of a user are represented into a tree which is called a user interest tree, the content and the structure of which can change simultaneously to adapt to the changes in a user's interests. This expression represents a user's specific and general interests as a continuurn. In some sense, specific interests correspond to shortterm interests, while general interests correspond to longterm interests. So this representation more really reflects the users' interests. The algorithm can automatically model a us er's multiple interest domains, dynamically generate the in terest models and prune a user interest tree when the number of the nodes in it exceeds given value. Finally, we show the experiment results in a Chinese Web Site. 展开更多
关键词 PERSONALIZATION user interest model vector space model agglomerate clustering method
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Performance Improvement of Multi-User Multiple-Input Multiple-Output Protocol for WLAN
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作者 Maha Bakalla Mznah Al-Rodhaan Yuan Tian 《Communications and Network》 2017年第2期124-141,共18页
The increase in the number of devices with a massive revolution in mobile technology leads to increase the capacity of the wireless communications net-works. Multi-user Multiple-Input Multiple-Output is an advanced pr... The increase in the number of devices with a massive revolution in mobile technology leads to increase the capacity of the wireless communications net-works. Multi-user Multiple-Input Multiple-Output is an advanced procedure of Multiple-Input Multiple-Output, which improves the performance of Wireless Local Area Networks. Moreover, Multi-user Multiple-Input Multiple-Output leads the Wireless Local Area Networks toward covering more areas. Due to the growth of the number of clients and requirements, researchers try to improve the performance of the Medium Access Control protocol of Multi-user Multiple-Input Multiple-Output technology to serve the user better, by supporting different data sizes, and reducing the waiting time to be able to transmit data quickly. In this paper, we propose a Clustering Multi-user Multiple-Input Multiple-Output protocol, which is an improved Medium Access Control protocol for Multi-user Multiple-Input Multiple-Out-put based on MIMOMate clustering technique and Padovan Backoff Algorithm. Utilizing MIMOMMate focuses on the signal power which only serves the user in that cluster, minimizes the energy consumption and increases the capacity. The implementation of Clustering Multi-user Multiple-Input Multiple-Output performs on the Network Simulator (NS2.34) platform. The results show that Clustering Multi-user Multiple-Input Multiple-Output protocol improves the throughput by 89.8%, and reduces the latency of wireless communication by 43.9% in scenarios with contention. As a result, the overall performances of the network are improved. 展开更多
关键词 clusterING MULTI-user MULTIPLE-INPUT Multiple-Output MULTI-user MULTIPLE-INPUT Multiple-Output MIMOMate Padovan BACKOFF Algorithm Wireless Local Arewa Network
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K-means算法在高速公路ETC数据分析中的应用 被引量:1
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作者 张添翼 杨涵 +1 位作者 田俊山 王歆远 《公路交通科技》 CAS CSCD 北大核心 2024年第6期199-206,共8页
为了更高效地利用高速公路ETC数据集并提升数据处理速度,深入分析ETC用户的主要特征和高速公路存在的潜在问题。以我国某省份某高速公路出入口2023年6月的ETC通行数据为例,通过Python编程语言对数据进行清洗,采用环形特征编码处理时间数... 为了更高效地利用高速公路ETC数据集并提升数据处理速度,深入分析ETC用户的主要特征和高速公路存在的潜在问题。以我国某省份某高速公路出入口2023年6月的ETC通行数据为例,通过Python编程语言对数据进行清洗,采用环形特征编码处理时间数据,并运用K-means聚类算法对数据进行处理。重点关注入口时间、出口时间、本省通行里程等指标,对用户的收费里程、速度以及行驶时间3个核心特征进行分析,借助聚类中心点和雷达图进行可视化展示。分析结果显示,傍晚时段的通行效率较低,晚间疲劳驾驶和午夜超速问题较为突出。根据通行里程分析,白天主要以短程和中程用户为主,长程用户倾向于在上午进入高速公路,同时,该高速公路存在大量的通勤车辆。在速度分析方面,低速组多为短途车辆。K-means聚类算法的应用使得数据处理过程快速且可靠,结合更多的ETC数据,可以进一步深入了解高速公路通行的主要群体和状况。研究成果可为制定差异化收费政策提供有力依据。例如,通过聚类分析进入高速公路的时间,确定高峰时段和低谷时段,适时提高高峰时段的费用,降低低谷时段的费用,从而提高通行效率、平衡路网流量。这具有重要的现实意义。 展开更多
关键词 智能交通 用户聚类 K-MEANS算法 高速公路ETC数据 海量数据
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基于时间戳间距的用户在线时长聚类方法
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作者 叶倩 高明 +2 位作者 田亮亮 韦雨萌 刘翼 《现代电子技术》 北大核心 2024年第16期47-50,共4页
在网络用户行为分析中,以时序维度为基础,研究用户网络行为的变化趋势,提出并挖掘更多有价值的信息,可为管理或商业决策提供有力支持。为此,文中提出一种基于时间戳间距的用户在线时长聚类方法,以用户访问日志文件中时间戳之间的间距作... 在网络用户行为分析中,以时序维度为基础,研究用户网络行为的变化趋势,提出并挖掘更多有价值的信息,可为管理或商业决策提供有力支持。为此,文中提出一种基于时间戳间距的用户在线时长聚类方法,以用户访问日志文件中时间戳之间的间距作为特征,首先将获取的日志数据进行预处理,获得用户的在线时长统计;然后采用K-Means聚类算法对用户进行聚类,并使用轮廓系数对K值进行评价分析,确定聚类K值范围,准确判定用户单次访问在线时长及类型。采用真实校园网用户访问日志数据对所提方法进行评价,实验结果表明,该方法的准确度达到0.9180,精确度达到0.7685,召回率达到0.8093。 展开更多
关键词 用户在线时长 用户聚类 K-MEANS聚类算法 数据预处理 时间戳间距 轮廓系数
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基于遗传优化神经网络的电力潜在敏感用户画像聚类算法 被引量:2
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作者 王海龙 李冠龙 +1 位作者 黄鑫磊 薛建德 《微型电脑应用》 2024年第1期138-140,144,共4页
为了解决电力潜在敏感用户画像聚类和识别结果准确度较低的问题,提出一种基于遗传优化神经网络的电力潜在敏感用户画像聚类算法。构建电力用户画像,精准刻画电力用户行为;选取电力用户画像的数值、时间、统计及聚类四种特征作为卷积神... 为了解决电力潜在敏感用户画像聚类和识别结果准确度较低的问题,提出一种基于遗传优化神经网络的电力潜在敏感用户画像聚类算法。构建电力用户画像,精准刻画电力用户行为;选取电力用户画像的数值、时间、统计及聚类四种特征作为卷积神经网络模型的输入,识别电力潜在敏感用户画像;采用改进遗传算法优化卷积神经网络,使得识别结果更为精准。实验结果表明,该方法能够聚类、识别电力潜在敏感用户画像,且聚类和识别的性能及准确度较好。 展开更多
关键词 遗传算法 卷积神经网络 用户画像 潜在敏感用户 聚类算法 相异度函数
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RIS辅助的无蜂窝大规模MIMO关键技术研究
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作者 张德坤 白宝明 《移动通信》 2024年第4期18-26,40,共10页
针对密集蜂窝组网干扰受限难题,无蜂窝大规模MIMO利用大规模宏分集,构建以用户为中心的新架构,大规模灵活协作显著提升每个用户性能。同时,无蜂窝辅以智能超表面技术,以低成本和低功耗极大提升网络容量。聚焦研究了RIS辅助的无蜂窝大规... 针对密集蜂窝组网干扰受限难题,无蜂窝大规模MIMO利用大规模宏分集,构建以用户为中心的新架构,大规模灵活协作显著提升每个用户性能。同时,无蜂窝辅以智能超表面技术,以低成本和低功耗极大提升网络容量。聚焦研究了RIS辅助的无蜂窝大规模MIMO天线校准和导频分配两个关键问题。针对大规模RAU校准难题,首先在最低校准信噪比和校准相干时间约束下,提出动态分簇的可自愈校准拓扑构建方法,然后为降低校准时域开销,设计了RAU簇内和簇间校准时序,研究了可扩展的天线校准算法,能实现任意多RAU联合相位校准。针对导频分配问题,首先提出基于空间高相关性的用户动态簇的构建新方法,然后提出用户簇内基于信道相关性最低和用户簇间最小复用概率的导频分配方法。仿真结果表明,提出的校准算法具有较小的校准误差和较好的扩展性。同时,提出的导频分配算法性能可逼近最大化容量导频分配算法,且复杂度大幅降低。 展开更多
关键词 无蜂窝大规模MIMO 分簇拓扑构建 互易性校准 用户动态簇 导频分配
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基于DTW K-medoids与VMD-多分支神经网络的多用户短期负荷预测 被引量:2
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作者 王宇飞 杜桐 +3 位作者 边伟国 张钊 刘慧婷 杨丽君 《中国电力》 CSCD 北大核心 2024年第6期121-130,共10页
多用户电力负荷预测是指根据历史负荷数据对多个用户或区域的电力负荷进行预测,可使电网企业掌握不同用户或区域的电力需求,以便更好地开展规划和实施调度优化等。然而由于各用户呈现出复杂多样的用电行为,采用传统方法难以进行统一建... 多用户电力负荷预测是指根据历史负荷数据对多个用户或区域的电力负荷进行预测,可使电网企业掌握不同用户或区域的电力需求,以便更好地开展规划和实施调度优化等。然而由于各用户呈现出复杂多样的用电行为,采用传统方法难以进行统一建模并实现快速准确预测。为此,构建了一种基于DTW Kmedoids与VMD-多分支神经网络的多用户短期负荷预测模型。首先,采用DTW K-medoids法进行用户负荷数据聚类,利用动态时间弯曲(dynamic time warping,DTW)计算数据间的距离,取代K-medoids算法中传统的欧氏距离度量方式,以改善多用户负荷聚类的效果;在此基础上,为充分表征负荷历史数据的长短期时序依赖特征,建立了一种基于变分模态分解(variational mode decomposition,VMD)-多分支神经网络模型的并行预测方法,用于多用户短期负荷预测;最后,使用某地区20个用户365天的负荷数据进行聚类、训练和测试实验,结果显示该模型结果的平均绝对误差和均方根误差等指标均较对比模型有较大幅度降低,表明该方法可有效表征多类用户的用电行为,提升多用户负荷预测效率和精度。 展开更多
关键词 多用户 负荷预测 DTW K-medoids聚类 变分模态分解(VMD) 多分支神经网络
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面向电动汽车用户的电价套餐模块化设计
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作者 肖白 刘佳涛 +3 位作者 杨士伟 焦明曦 王大亮 姜卓 《电网技术》 EI CSCD 北大核心 2024年第11期4544-4552,I0037,共10页
合理的电价套餐能够有效地调动电力用户主动参与需求响应的积极性,在减少供电公司的基础建设投资和运行压力的同时,提升售电公司的收益,降低用户的用电费用。针对当前电力市场中用户类型多样,市场竞争压力日增,各方对电价套餐的需求各异... 合理的电价套餐能够有效地调动电力用户主动参与需求响应的积极性,在减少供电公司的基础建设投资和运行压力的同时,提升售电公司的收益,降低用户的用电费用。针对当前电力市场中用户类型多样,市场竞争压力日增,各方对电价套餐的需求各异,且缺少合适的电价套餐以供选择的情况,提出了一种面向电动汽车(electric vehicle,EV)用户的电价套餐模块化设计方法。首先,通过采用两阶段聚类法生成典型EV用户的充电负荷曲线来确定其充电需求,其中第一阶段使用凝聚层次聚类算法,第二阶段使用K-means聚类方法。其次,运用大规模定制理论并根据典型EV用户的充电需求来设置齐备的电价套餐模块,并计算不同EV用户的个性化充电需求与各模块之间的综合相关度矢量。然后,根据该相关度矢量为每个EV用户分别选择适合的个性化模块组,并逐一配置模块组的相应个性化属性及特征值。最后,结合所选用模块及其属性合特征值配置情况构造考虑需求响应的模块化电价套餐的定价模型。算例结果表明了所提出的电价套餐设计方法是正确、可行的,能够达成供、售电公司以及用户三方共赢的局面。 展开更多
关键词 电价套餐 EV用户 K-MEANS聚类 大规模定制理论 模块化设计
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基于系列智能算法的某省天然气用户用气规律分类与短期调峰需求预测
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作者 张玉萍 孙广宇 +1 位作者 徐嘉祥 杨文轩 《广东化工》 CAS 2024年第9期83-87,95,共6页
天然气管网系统庞大、用户繁多,在用户用气习惯不明确和调峰需求量模糊的情况下,管网的运行调度面临巨大挑战。本文基于某省天然气管网2018年至2020年用户用气数据,利用k-means++算法对不同用户的用气习惯进行初步类别划分,而后使用BP... 天然气管网系统庞大、用户繁多,在用户用气习惯不明确和调峰需求量模糊的情况下,管网的运行调度面临巨大挑战。本文基于某省天然气管网2018年至2020年用户用气数据,利用k-means++算法对不同用户的用气习惯进行初步类别划分,而后使用BP神经网络对典型用户的特征向量进行学习、分类,结合监督学习和无监督学习两种方式,获取三种典型用户。基于上述分类结果,利用典型用户三年的调峰需求量数据,分别通过七种智能算法模型对用户调峰需求数据进行了预测,旨在得到可靠的用户调峰需求量短期预测模型。模型计算结果表明,七种算法对短期调峰预测均有可靠的性能,其中GDB模型拥有更快的计算速度和更高的准确性,并且对于长期调峰预测具有一定的可行性。 展开更多
关键词 调峰预测 用户分类 聚类分析 神经网络
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基于用户评论文本挖掘的我国早期教育App的发展现状和对策
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作者 程渝洋 单洁 马玉慧 《科技和产业》 2024年第14期72-78,共7页
随着移动终端的普及,越来越多的学龄前儿童开始使用早期教育App进行学习,早期教育App已成为学龄前儿童重要的学习资源,这就必然要提高早期教育App的质量,了解用户需求。在线评论真实反映了用户对产品的满意度,通过对评论进行分析,能够... 随着移动终端的普及,越来越多的学龄前儿童开始使用早期教育App进行学习,早期教育App已成为学龄前儿童重要的学习资源,这就必然要提高早期教育App的质量,了解用户需求。在线评论真实反映了用户对产品的满意度,通过对评论进行分析,能够了解用户对早教App的态度,为以后的改进提供建议。采用社会网络分析、LDA(Latent Dirichlet Allocation)主题聚类分析和情感分析技术对我国早期教育App用户评论文本进行研究,探讨其发展现状和存在问题,并提出改进建议。研究发现,我国早期教育App能够基本满足用户学习需求,但存在学科分布不合理和性能、内容设计不足等问题,影响用户正常使用。 展开更多
关键词 早教App 用户评论 主题聚类 情感分析 社会网络分析
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