检索结果-内蒙古大学图书馆

Inuence maximization algorithm based on genetic algorithm

Journal of Computational Information systems 2014年第21期10卷 9255-9262页

作者： Guo, Jingfeng Liu, Yuanying Shen, Jiali Wei, Zhenzhen Lv, Jiaguo College of Information Science and Engineering Yanshan University Qinhuangda China College of Information Technology Hebei University of Economics and Business Shijiazhuang China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao China

The inuence maximization problem is defined as providing a given initial integer k, mining top-k inuential nodes from a social network such that the spread of inuence in the network is maximized. Some existing studies are based on Greedy algorithm, but their time complexity is very high. In this paper, a different method based on Genetic Algorithms, denoted as MAGA is proposed. In the MAGA algorithm, the set of k nodes is seen as a candidate solution, and the expected inuence value as fitness. Use the genetic algorithm to get the optimal solution. Experiments show that the algorithm achieved a balance in inuence spread and running time.

关键词： Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

A PTV method based on SIFT feature points matching for velocimetry measurement of oil-water two-phase flow in horizontal pipelines

International Journal of Signal Processing, Image Processing...

引用

International Journal of Signal Processing, Image Processing and Pattern Recognition 2015年第12期8卷 195-206页

作者： Kong, Weihang Li, Lei Kong, Lingfu Li, Yingwei Xie, Na School of Information Science and Engineering Yanshan University QinhuangdaoHebei China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Hebei China Information Department of Library Yanshan University QinhuangdaoHebei China

Due to the advantages of scale invariant feature transform (SIFT) feature points on the invariant to image scale, brightness, rotation, occlusion, noise and so on, this paper proposes a Particle Tracking Velocimetry (PTV) method, based on SIFT feature points matching for velocity measurement of oil-water two-phase flow in horizontal pipelines. The oil-water two-phase flow with large droplet diameter, oil droplets overlap, ununiform lighting, and the centroid position of oil droplets can’t be obtained only by using traditional PTV methods through morphological processing. However, in this paper, the algorithm can directly achieve the average velocity of the flow field according to the positions of correctly matched SIFT feature points, and there is no need to extract the centroid coordinates of each oil droplet. The experimental results show that the proposed algorithm not only can be used in the average velocity measurement of oil-water two- phase flow in horizontal pipelines, but also can reach 95% in the measuring accuracy when the matching feature points are enough sufficient. © 2015 SERSC.

关键词： Velocity measurement

来源：评论

学校读者我要写书评

暂无评论

Occlusion avoidance approach based on depth image of visual object

引用

ICIC Express Letters, Part B: Applications 2015年第11期6卷 3103-3108页

作者： Zhang, Shihui Sang, Yu Zhang, Xiaojun School of Information Science and Engineering Yanshan University No. 438 Hebei Avenue Qinhuangdao China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province No. 438 Hebei Avenue Qinhuangdao China E and A College Hebei Normal University of Science and Technology No. 360 West Hebei Street Qinhuangdao China

Occlusion avoidance is a more challenging problem in visual field. An occlusion avoidance approach based on depth image of visual object is proposed in this paper. Firstly, the occlusion detection is implemented for the depth image of visual object in current view, and then the occlusion boundary and nether adjacent boundary are obtained to construct occlusion region. Secondly, the occlusion region is segmented into several sub-regions by connecting the corner of occlusion boundary with its nether adjacent boundary point, and the triangular mesh model of each sub-region is established. Thirdly, the candidate observation direction set is determined by utilizing the normal vector of each triangle in triangular mesh model. Finally, the next best view is confirmed based on the candidate observation direction set to realize the occlusion avoidance function. Compared with the existing methods, the proposed approach does not need the priori knowledge of visual object or limit the camera position on a fixed surface. Experimental results demonstrate its feasibility and effectiveness. © 2015 ICIC International.

关键词： Mesh generation

来源：评论

学校读者我要写书评

暂无评论

Reinforced Heterogeneous Graphlet Design for Knowledge Graph Representation Learning

SSRN

引用

SSRN 2023年

作者： Gong, Jibing Lin, Yuting Zhao, Yi Lin, Tianyu Fang, Xiaohan Feng, Xinchao Peng, Jiquan School of Information Science and Engineering Yanshan University Qinhuangdao066004 China The Key Laboratory for Computer Virtual Technology System Integration of Hebei Province Yanshan University Qinhuangdao066004 China

Knowledge Graphs have been practical tools to represent and integrate plentiful structural and semantic information in mainstream industrial scenarios. While promising, the heterogeneity and complexity of KGs pose a formidable obstacle, especially for graph representation learning. Most existing KG embedding models omit the dynamic high-order connectivity patterns, and heavily rely on the handcrafted patterns to handle the complex semantic relationships, thereby limiting their ability to adaptively capture nuanced and intricate relationships of knowledge graphs in different tasks. To fill this gap, we present ReHGD — a model designed for KGs that focuses on adaptively designing typed graphlets through a cooperative Multi-agent Reinforcement Learning algorithm. This approach can learn more discriminative graph representations tailored to specific downstream tasks. Specifically, ReHGD engages in the creation of typed graphlets through a two-stage process: it (1) establishes a reinforced chain design module to generate chains without predefined rules, and (2) employs a buffer-aware sampling technique to derive episodic chains from prior experiences. Subsequently, motifs are deduced by applying commute count and Hadamard product operations to the episodic chain-based subgraphs. Finally, ReHGD utilize chain and motif aggregations to learn graph representations. Experimental results on three real-world KGs show that ReHGD outperforms baselines on entity classification. © 2023, The Authors. All rights reserved.

关键词： Knowledge graph

来源：评论

学校读者我要写书评

暂无评论

SYVR virtual Equipment Manufacturing Simulation

SYVR Virtual Equipment Manufacturing Simulation

引用

International Conference on virtual Reality and Visualization (ICVRV)

作者： Yuhan Liu Yong Tang Qian Sun Shiny VR Yanshan University College of Information Science and Engineering Qinhuangdao China Yanshan University The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao China

ISBN: (纸本)9781538684986;9781538684979

SYVR is a real-time simulation graphic engine focusing on equipment manufacturing. It is based on decades of research works of physics simulations, is able to provide services like real-time simulation for key parts of devices, large-scale com-plicated situation simulation, virtual experiment, operational training, visualization of concept design and etc., which con-sist of the whole process of virtual manufacturing and simulation. SYVR can provide comprehensive technology support for industrial 3-dimensional data, accelerate applications of VR to all aspects of industry, cut down development costs of equipment manufacturing significantly, highly increase effi-ciency of equipment design, and promote development of equipment manufacturing.

关键词： Conferences virtual reality Visualization

来源：评论

学校读者我要写书评

暂无评论

Improved BP classifier via distance for sample reduction

引用

Journal of computers (Taiwan) 2019年第2期30卷 1-13页

作者： Wen, Jia Deng, Jia Liu, Peng-Fei Wang, Hong-Jun Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Yanshan University Qinhuangdao China School of Information Science and Engineering Yanshan University Qinhuangdao China State Key Laboratory of Software Engineering of Hebei Province Yanshan University Qinhuangdao China

The BP neural network algorithm is a commonly used technique in the classification field of pattern recognition, which iterates training samples continuously to obtain the decision boundary, until the error reaches the convergence precision. However, due to the extensive redundancy of training samples, this carpet-like training method can easily lead to slow network convergence and low classification performance. In this paper, from the view of sample, a novel BP training method called improved BP Classifier algorithm using Distance for Sample Reduction (DRBP) is proposed. Through the sample weight to get the new training sample, which are the near of the classification interface like support vector, and then iterative training BP classifier to solve the classification issue. The main function of this method is to keep the original sample information, realize the sample reduction, and improve the generalization ability of the BP neural network. First, point sets is used to visualize the training process. And then use 10 sets of the University of California Irvine (UCI) to verify the effectiveness and superiority of our experiments. Finally through Cross-validation, the classification error rate of 10 sets of UCI datasets tested by DRBP training method is lower than that of standard BP neural network (STBP). So the result of the experiment showed that the method of the combined distance sample reduce with BP network can significantly enhance the generalization ability of BP network. © 2019 computer Society of the Republic of China. All rights reserved.

关键词： Classification (of information)

来源：评论

学校读者我要写书评

暂无评论

Mining important nodes in directed-weighted software network based on semi-global structure information

引用

ICIC Express Letters 2015年第10期9卷 2859-2866页

作者： Ren, Jiadong Wu, Hongfei Yin, Tengteng Liu, Yang He, Haitao College of Information Science and Engineering Yanshan University No. 438 West Hebei Ave. Qinhuangdao China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Yanshan University No. 438 West Hebei Ave. Qinhuangdao China

Software’s control flow graph can be treated as a complex software network, and a tiny fraction of key function nodes has considerable influence on the stability, reliability and robustness of the network. Identifying the top-k key nodes accurately and effectively has become an important topic in software engineering. In this paper, directedweighted function dependency network (DWFDN) is adopted to represent the function and relationship of function calling or dependency. The weight on a direct edge indicates the frequency of function calling. Weighted semi-global structure information (the weight, the relative position of a function node and the topological structure among its neighbor nodes) is taken into consideration in our approach. From the perspective of accumulating and propagating vulnerabilities, key function callers and function callees are mined respectively. Case studies on real software date show the utility of the approach. © 2015, ICIC International.

关键词： Software reliability

来源：评论

学校读者我要写书评

暂无评论

An improved Wu-Huberman community discovery algorithm based on edge points

引用

ICIC Express Letters 2013年第11期7卷 2949-2955页

作者： Guo, Jingfeng Wang, Xiaolin Zuo, Mengfei Lv, Jiaguo College of Information Science and Engineering Yanshan University No. 438 Hebei Ave. Qinhuangdao 066004 China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Yanshan University No. 438 Hebei Ave. Qinhuangdao 066004 China

There are two critical questions in the Wu-Huberman algorithm: one is picking two poles and the other is setting the threshold. By further studying the two questions, we present a method that makes the discovery of communities more precise and the scope of application of the algorithm wider. The method picks the edge nodes of two communities as two poles and finds the largest gap using the core nodes of communities, which can discover communities of arbitrary size instead of roughly the same size. © 2013 ISSN 1881-803X.

关键词： Poles

来源：评论

学校读者我要写书评

暂无评论

An efficient Subspace Clustering Algorithm based on Attribute Relativity and DBSCAN

引用

ICIC Express Letters 2014年第6期8卷 1677-1682页

作者： Zeng, Qiang Bai, Yunyue He, Haitao Ren, Jiadong College of Information Science and Engineering Yanshan University No. 438 Hebei Ave. Qinhuangdao 066004 China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Yanshan University No. 438 Hebei Ave. Qinhuangdao 066004 China

In the high-dimensional data traditional clustering algorithms tend to break down because of the curse of dimensionality, high cost of time, etc. This paper proposes a novel algorithm AReSUBCLU, an Effective Subspace Clustering Algorithm based on Attribute Relativity and DBSCAN. Active attribute is defined to reduce the dimension of data, and a subspace search tree which is constructed by attribute correlation matrix is defined to generate subspaces. Firstly, this method uses DBSCAN with the technique of weighted threshold to cluster on every active attribution. Secondly, the correlation matrix is constructed by computing the covariance of attributes. And the subspace search tree is constructed by the matrix which is used to measure the relativity of attributions. The set of nodes in each root branch of the tree is the interesting subspaces that the algorithm discovers. Finally, the subspace clusters are obtained through merging every cluster of active dimension with the usage of similarity of cluster. Evaluation with synthetic and real-world datasets demonstrates that AReSUBCLU has a good clustering quality, and capability of discovering subspace clusters of arbitrary shapes. © 2014 ISSN 1881-803X.

关键词： Clustering algorithms

来源：评论

学校读者我要写书评

暂无评论

LoBa-Min-Min-SPA: Grid load balance using SPA

引用

Open Automation and Control systems Journal 2013年第1期5卷 87-95页

作者： Zhang, Zhongping Wen, Lijuan Wang, Zhiping College of Information Science and Engineering Yanshan University Qinhuangdao Hebei 066004 China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao Hebei 066004 China Foreign Language College of Dalian Jiaotong University Dalian Liaoning 116052 China

In the grid environment, there are a large number of grid resources scheduling algorithms. According to the existing Min-Min scheduling algorithm in uneven load, and low resource utilization rate, we put forward LoBa-Min-Min algorithm, which is based on load balance. This algorithm first used Min-Min algorithm preliminary scheduling, then according to the standard of reducing Makespan, the tasks on heavy-loaded resources would be assigned to resources that need less time to load balance, raise resource utilization rate, and achieve lesser completion time. We used benchmark of instance proposed by Braun et al. to prove feasibility and effectiveness of the algorithm. At Last, We introduced the SPA and gave the experimental results of Min-Min-SPA and LoBa-Min-Min-SPA. © Zhang et al.;Licensee Bentham Open.

关键词： Grid computing

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：