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2021 International Conference on Intelligent Computing, Automation and Applications (ICAA)最新文献

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Processing Approximate KNN Query Based on Data Source Selection 基于数据源选择的近似KNN查询处理
Liang Zhu, Peng Li, Yonggang Wei, Xin Song, Yu Wang
A KNN query over a relation is to find its $K$ nearest neighbors/tuples from a dataset/relation according to a distance function. In this paper, we discuss approximate KNN query processing based on the selection of many data sources with various dimensions. We propose algorithms to construct a UBR- Tree and a Centroid Base for selecting related data sources and retrieving $K$ NN tuples. For a $K$ NN query $Q$, (1) the related data sources are selected by using the Centroid Base, (2) these data sources are sorted according to their representative tuple in the Centroid Base, (3) local $K$ NN tuples in the related data sources are retrieved, and (4) a heap structure is used to merge the local $K$ NN tuples to form global $K$ NN tuples of $Q$. Extensive experiments over low-dimensional and high-dimensional datasets are conducted to demonstrate the performances of our proposed approaches.
对一个关系的KNN查询是根据距离函数从一个数据集/关系中找到它的$K$近邻/元组。在本文中,我们讨论了基于选择多个不同维度的数据源的近似KNN查询处理。我们提出了构建UBR- Tree和质心库的算法,用于选择相关数据源和检索$K$ NN元组。对于$K$ NN查询$Q$,(1)使用质心库选择相关数据源,(2)根据质心库中的代表性元组对这些数据源进行排序,(3)检索相关数据源中的局部$K$ NN元组,(4)使用堆结构将局部$K$ NN元组合并形成$Q$的全局$K$ NN元组。在低维和高维数据集上进行了广泛的实验,以证明我们提出的方法的性能。
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引用次数: 0
Study of Canopy and K-Means Clustering Algorithm Based on Mahout for E-commerce Product Quality Analysis 基于Mahout的Canopy和K-Means聚类算法在电子商务产品质量分析中的研究
Peizhang Xie, Minming Mao, Xuguang Jin, Dong Chen, Mengyi Guo
With the rapid development of “Internet +”, mobile application and communication technology, e-commerce has increasingly become the main shopping way for consumers in China. Aiming at quality keywords, this paper designs a distributed data clustering system based on Hadoop and mahout. In order to overcome the randomness, low accuracy and many iterations of K-Means algorithm, Canopy and K-Means Clustering Algorithm based on Mahout is designed by using the advantages of Canopy algorithm, that is, no need to specify the number of clusters, high efficiency and conciseness Clustering keywords. Based on the algorithm, good results have been obtained.
随着“互联网+”、移动应用和通信技术的快速发展,电子商务日益成为中国消费者的主要购物方式。针对质量关键词,本文设计了一个基于Hadoop和mahout的分布式数据聚类系统。为了克服K-Means算法的随机性、精度低、迭代多等缺点,利用Canopy算法不需要指定聚类个数、聚类关键词效率高、简洁等优点,设计了基于Mahout的Canopy和K-Means聚类算法。该算法取得了较好的效果。
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引用次数: 2
Output Synchronization for Networked Strict-feedback Systems in the Presence of Uncertainties 存在不确定性时网络严格反馈系统的输出同步
Ming Lu, Miao Yu, Zhijun Qiao, Duanshuai Li, Junmin Peng
This literature investigates the output synchronization control of multiple strict-feedback systems with unknown parameter, uncertain control directions and disturbance under directed communication graph. We design a decentralized controller step by step for each agent such that their outputs are synchronized and the closed-loop system is guaranteed to be bounded. As an extension of our previous work, in this literature, disturbance is considered in the agent's dynamic. It is proved that the Nussbaum item is effective not only for seeking control direction automatically but also for guaranteeing the boundedness of the overall system without additional counteraction of the disturbance. The effectiveness of the proposed scheme has been verified by simulation results.
研究了有向通信图下参数未知、控制方向不确定、存在干扰的多严格反馈系统的输出同步控制问题。我们为每个智能体逐步设计分散式控制器,使它们的输出同步,并保证闭环系统是有界的。作为我们以前工作的延伸,在这篇文献中,干扰被考虑到代理的动态。证明了Nussbaum项不仅能有效地自动寻找控制方向,而且能有效地保证整个系统的有界性,而不需要扰动的额外抵消。仿真结果验证了该方案的有效性。
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引用次数: 0
The Compactness of the Hyperspace 2X with the Locally Finite Topology 局部有限拓扑下超空间2X的紧性
Meili Zhang, Hongmei Pei, Weili Liu, Yue Yang
Let X be topological space. A vietoris-type topology, called the locally finite topology, is defined on the hyperspace $2^{X}$ of all closed, nonempty subsets of X. In this paper, we discuss compactness of the locally finite topology on hyperspace. And give the important conclusion, therefore this develops E.Micheal, J.Keesling some results.
设X是拓扑空间。在X的所有闭非空子集的超空间$2^{X}$上定义了一个vietoris型拓扑,称为局部有限拓扑。本文讨论了局部有限拓扑在超空间上的紧性。并给出了重要的结论,从而发展了e.m heal, j.k esling的一些成果。
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引用次数: 0
Research on Spatial-temporal Differentiation and Driving Forces of Green Economic Efficiency in the Yangtze River Economic Belt Based on Geographic Detectors 基于地理探测器的长江经济带绿色经济效率时空分异及驱动力研究
Shuguang Liu, L. Song, Yue Huang
The research is based on the undesirable super-efficiency EBM model to measure the GEE of 108 cities in the YREB from 2003 to 2018, uses Geographical Information System to characterize the temporal and spatial evolution of the GEE, and applies the geographic detector model to further reveal the spatial heterogeneity of its driving forces. The results show that: (1)The GEE of the YREB took 2013 as the inflection point, showing two phases of volatility decline period and rapid rise period, and reflecting the spatial differentiation characteristics of “upstream-midstream-downstream” urban agglomeration. (2)The core driving forces for the improvement of GEE in the YREB include urbanization, consumption level, financial industry development, technological innovation and Internet penetration rate.(3)The local scale of the driving forces for GEE improvement is significantly different. The core driving forces of the upstream are education investment, urbanization, Internet penetration rate and transportation infrastructure; and education investment, industrial structure and city scale in the midstream; and industrial structure, consumption, technological innovation, economic development level in the downstream. Therefore, upstream, midstream, and downstream must seek to adapt to the situation and local conditions to improve the GEE.
本研究基于非期望超效率实证模型对2003 - 2018年长江经济带108个城市的城市生态环境进行测度,利用地理信息系统对城市生态环境时空演化特征进行表征,并利用地理探测器模型进一步揭示城市生态环境驱动力的空间异质性。结果表明:(1)长江经济带GEE以2013年为拐点,呈现出波动性下降期和快速上升期两个阶段,反映出“上游-中游-下游”城市群空间分异特征;(2)城镇化、消费水平、金融业发展、技术创新和互联网普及率是长城路经济带环境承载力提升的核心驱动力。(3)地方层面环境承载力提升驱动力差异显著。上游的核心驱动力是教育投资、城镇化、互联网普及率和交通基础设施;中游地区的教育投资、产业结构和城市规模;与下游产业结构、消费、技术创新、经济发展水平有关。因此,上游、中游和下游都必须因地制宜,努力改善生态环境。
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引用次数: 0
Application of the Random Forest Kernel in Nonparametric Regression Model with Spherical Variables 随机森林核在球变量非参数回归模型中的应用
Huiqun Gao, Xu Qin
In this paper, we apply the random forest kernel to nonparametric regression model with spherical and linear variables. Validate the new model with simulated data and actual airfoil noise data. Comparing with the Gaussian kernel and the linear-circular kernel, the experimental results show that the random forest kernel has stable performance and fast computation speed, and the random forest kernel has a better fitting effect in high dimension.
本文将随机森林核应用于具有球形和线性变量的非参数回归模型。用仿真数据和实际翼型噪声数据验证新模型。实验结果表明,与高斯核和线性圆核相比,随机森林核具有稳定的性能和快速的计算速度,并且在高维上具有更好的拟合效果。
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引用次数: 0
Blockchain Plus Finance: Application, Dilemma and Solution 区块链+金融:应用、困境与解决
Haoqi Yu, Jiangshen Pan, Jinjian Yang
Blockchain technology has attracted great attention in various fields because of its advantages of distributed network. Its rational application in enterprise's financial activities can optimize financial processes and control operating costs; improve the quality of financial information, reduce information asymmetry; promote the transformation and progress of financial personnel. But there may be difficulties in the practical application of new technology, and this paper will put forward feasible solutions based on these problems.
区块链技术以其分布式网络的优势受到了各个领域的广泛关注。它在企业财务活动中的合理应用,可以优化财务流程,控制经营成本;提高财务信息质量,减少信息不对称;促进财务人员转型进步。但新技术在实际应用中可能存在困难,本文将针对这些问题提出可行的解决方案。
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引用次数: 0
Chinese Named Entity Recognition for a Power Customer Service Intelligent Q&A System 电力客户服务智能问答系统的中文命名实体识别
Ning Wu, Hongying Zhao, Youlang Ji, Shaochen Sun
Power customer service intelligent Q&A system can greatly improve the efficiency of power customer service and reduce labor costs. In order to deal with the questions that need to be solved by reasoning, it is necessary to build the power customer service knowledge graph and accurately understand the questions. One of the key tasks is to implement a named entity recognizer using the historical log data of power customer service Q&A. Recently, lattice based neural networks have gained great advantages in Chinese named entity recognition. However, lattice based models rely heavily on an external predetermined dictionary, and the quality of the dictionary may interfere with entity boundary learning. As the power customer service Q&A is a form of oral conversation., it is difficult to build the specialized dictionary, which seriously restricts the application of the original menthod of lattice structure based neural network for Chinese named entity recognition in the field of power customer service. Therefore, this paper proposes a method of using entity boundary locally in lattice based neural networks for Chinese named entity recognition. Through joint learning of entity boundary and entity recognition, without any external dictionary, experiments on data sets in the field of power customer service show that this method has very good potential.
电力客服智能问答系统可以大大提高电力客服效率,降低人工成本。为了处理需要通过推理解决的问题,有必要构建电力客户服务知识图谱,准确理解问题。关键任务之一是使用电力客户服务问答的历史日志数据实现命名实体识别器。近年来,基于点阵的神经网络在中文命名实体识别中取得了很大的优势。然而,基于晶格的模型严重依赖于外部预定字典,字典的质量可能会干扰实体边界学习。作为客户服务的动力,问答是一种口头对话的形式。这严重制约了基于点阵结构的神经网络中文命名实体识别方法在电力客户服务领域的应用。为此,本文提出了一种网格神经网络中局部使用实体边界的中文命名实体识别方法。通过实体边界和实体识别的联合学习,在不需要任何外部字典的情况下,对电力客户服务领域的数据集进行实验,表明该方法具有很好的潜力。
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引用次数: 1
The Optimization of Microgrid Distribution Based on PSO 基于粒子群算法的微电网配电优化
Aidong Xu, Runhui Zhao, Zhongqi Mao, Hong Wen, Yixin Jiang, Lingzhi Fei, Peiyao Wang, Yunan Zhang
It is important to predict microgrid user's behaviour and the power generation quota of the microgrid for the optimal interaction of power distribution between microgrid generators and users. In this paper, PSO algorithm is used to get the optimal solution of the micro network transaction model, and the weight proportion of each cost attribute of the graph node is calculated through the normalization function and weight proportion formula by collection and analysis the producing electricity and demand data of microgrid system under the edge computing module. The experiment under a small distributed autonomous microgrid proves the effectiveness of the novel method.
预测微网用户的行为和微网的发电配额对于实现微网发电机组和用户之间的最佳配电交互具有重要意义。本文采用粒子群算法得到微网交易模型的最优解,并通过收集和分析微网系统在边缘计算模块下的发电量和需求数据,通过归一化函数和权重比例公式计算图节点各成本属性的权重比例。在小型分布式自治微电网下的实验验证了该方法的有效性。
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引用次数: 0
Multi-label Text Classification and Text Adversarial Attack 多标签文本分类与文本对抗攻击
Yi-Fan Song, Zhenyan Liu, Chunxia Zhang
Multi-label classification is an extension of multi-class classification. For multi-label problem, each instance may not be restricted to have only one label. In this paper, the methods to solve multi-label classification are divided into four aspects which are binary relevance method, label combination method, classifier chain and ensemble classifier chain. In order to enhance the performance of the text classifier, text adversarial attack should be used to enrich the training dataset. Thus, the related works with text adversarial attack are also introduced. In the end, we also explore some potential future issues in multi-label text classification and text adversarial attack.
多标签分类是多类分类的扩展。对于多标签问题,可以不限制每个实例只有一个标签。本文将解决多标签分类问题的方法分为二元关联法、标签组合法、分类器链和集成分类器链四个方面。为了提高文本分类器的性能,应该使用文本对抗攻击来丰富训练数据集。在此基础上,介绍了文本对抗性攻击的相关工作。最后,我们还探讨了在多标签文本分类和文本对抗性攻击方面可能存在的问题。
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引用次数: 1
期刊
2021 International Conference on Intelligent Computing, Automation and Applications (ICAA)
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