检索结果-内蒙古大学图书馆

Image clustering segmentation based on SLIC superpixel and transfer learning

Pattern Recognition and Image Analysis 2017年第4期27卷 838-845页

作者： Li, X.X. Shen, X.J. Chen, H.P. Feng, Y.C. College of Computer Science and Technology Jilin University ChangchunJilin130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University ChangchunJilin130012 China

Traditional fuzzy C-means clustering algorithm has poor noise immunity and clustering results in image segmentation. To overcome this problem, a novel image clustering algorithm based on SLIC superpixel and transfer learning is proposed in this paper. In the proposed algorithm, SLIC superpixel method is used to improve the edge matching degree of image segmentation and enhances the robustness to noise. Transfer learning is adopted to correct the image segmentation result and further improve the accuracy of image segmentation. In addition, the proposed algorithm improves the original SLIC superpixel algorithm and makes the edge of the superpixel more accurate. Experimental results show that the proposed algorithm can obtain better segmentation results. © 201., Pleiades Publishing, Ltd.

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

A hybrid feature selection algorithm for microarray data

引用

Concurrency and computation: Practice and Experience 2018年

作者： Zheng, Yuefeng Li, Ying Wang, Gang Chen, Yupeng Xu, Qian Fan, Jiahao Cui, Xueting College of Computer Science and Technology Jilin University Changchun130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China BODA College of Jilin Normal University SiPing China

For each microarray data set, only a small number of genes are beneficial. Due to the high-dimensional problem, gene selection research work remains a challenge. In order to solve the high-dimensional problem, we propose a dimensionality reduction algorithm named K Value Maximum Relevance Minimum Redundancy Improved Grey Wolf Optimizer (KMR2IGWO). First, in the processing of KMR2, the K genes are selected. Second, the K genes are initialized by two ways according to random selection feature and different proportions of selection feature. Finally, the IGWO algorithm selects the optimal classification accuracy and the optimal combination of gene by adjusting the parameters of fitness function. The algorithm has a significant dimensionality reduction effect and is suitable for high-dimensional data sets. Experimental results show that the proposing KMR2IGWO strategy significantly reduces the dimension of microarray data and removes the redundant features. On the 1. microarray datasets, compared with the four algorithms mRMR+PSO, mRMR + GA, mRMR + BA, mRMR + CS, the proposed algorithm has higher performance in classification accuracy and feature subset length. © 201. John Wiley & Sons, Ltd.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Corrigendum to: Multi-Swarm Cuckoo Search Algorithm withQ-Learning Model

引用

The Computer Journal 2022年第7期65卷 1938-1938页

作者： Li, Juan Xiao, Dan-dan Zhang, Ting Liu, Chun Li, Yuan-xiang Wang, Gai-ge School of Artificial Intelligence Wuhan Technology and Business University Wuhan 430065 China School of Artificial Intelligence Wuchang University of Technology Wuhan 430223 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University No. 2699 Qianjin Street Gaoxin District Changchun Jilin China 130012 School of Computer Wuhan University No. 299 Bayi Street Wuchang District Wuhan Hubei China 430072 Department of Computer Science and Technology Ocean University of China No. 238 Songling Street Laoshan District Qingdao Shandong China 266100 Institute of Algorithm and Big Data Analysis Northeast Normal University No. 5268 Renmin Street Nanguan District Changchun Jilin China 130117

来源：评论

学校读者我要写书评

暂无评论

A Two-Dimensional Improvement for Farr-Gao Algorithm

引用

Journal of Systems Science & Complexity 2016年第5期29卷 1382-1399页

作者： DONG Tian School of Mathematics Key Laboratory of Symbolic Computation and Knowledge Engineering (Ministry of Education) Jilin University

Farr-Gao algorithm is a state-of-the-art algorithm for reduced Gr?bner bases of vanishing ideals of finite points, which has been implemented in Maple as a build-in command. This paper presents a two-dimensional improvement for it that employs a preprocessing strategy for computing reduced Gr?bner bases associated with tower subsets of given point sets. Experimental results show that the preprocessed Farr-Gao algorithm is more efficient than the classical one.

关键词： Grobner basis GrSbner escalier Newton interpolation basis tower set vanishing ideal.

来源：评论

学校读者我要写书评

暂无评论

A new SAT Encoding Scheme for Exactly-one Constraints

引用

Journal of Physics: Conference Series 2019年第1期1288卷

作者： Jiatong Cai Yating Su Xixi Yang Jionghao Min Yong Lai College of Software Jilin University Changchun P.R. China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun P.R. China

Exactly-one constraints have comprehensive applications for the fields of artificial intelligence and operations research. For many encoded SAT problems generated by the existing encoding schemes of exactly-one constraints, the state-of-the-art knowledge compilers cannot complete compilation. In this paper, we propose a new encoding scheme of exactly-one constraints. We introduce two-dimensional auxiliary variables (represented as a matrix) to denote the constraint that exactly one of some variables can be assigned as true. The clauses generated by our scheme is significantly less than those generated by three other existing encoding schemes. The experimental results on the exact cover problems show that the encoded CNF formulas generated by our scheme requires less compilation time, compared with the other three coding schemes.

关键词：

来源：评论

学校读者我要写书评

暂无评论

The Equivalent Representation of the Breadth-One D-Invariant Polynomial Subspace and Its Discretization

引用

Journal of Systems Science & Complexity 2016年第5期29卷 1436-1445页

作者： JIANG Xue ZHANG Shugong Institute of Mathematics Key Laboratory of Symbolic Computation and Knowledge Engineering (Ministry of Education) Jilin University

This paper demonstrates the equivalence of two classes of D-invariant polynomial subspaces, i.e., these two classes of subspaces are different representations of the breadth-one D-invariant subspace. Moreover, the authors solve the discrete approximation problem in ideal interpolation for the breadth-one D-invariant subspace. Namely, the authors find the points, such that the limiting space of the evaluation functionals at these points is the functional space induced by the given D-invariant subspace, as the evaluation points all coalesce at one point.

关键词： Breadth-one D-invariant polynomial subspace discrete approximation problem idealinterpolation.

来源：评论

学校读者我要写书评

暂无评论

Building trust networks in the absence of trust relations

引用

Frontiers of Information Technology & Electronic engineering 2017年第10期18卷 1591-1600页

作者： Xin WANG Ying WANG Jian-hua GUO College of Computer Science and Technology Jilin University Changchun 130012 China School of Computer Technology and Engineering Changchun Institute of Technology Changchun 130012 China School of Mathematics and Statistics Northeast Normal University Changchun 130024 China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Changchun 130012 China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology Guilin 541004 China

User-specified trust relations are often very sparse and dynamic, making them difficult to accurately predict from online social media. In addition, trust relations are usually unavailable for most social media *** issues pose a great challenge for predicting trust relations and further building trust networks. In this study,we investigate whether we can predict trust relations via a sparse learning model, and propose to build a trust network without trust relations using only pervasively available interaction data and homophily effect in an online world. In particular, we analyze the reliability of predicting trust relations by interaction behaviors, and provide a principled way to mathematically incorporate interaction behaviors and homophily effect in a novel framework,b Trust. Results of experiments on real-world datasets from Epinions and Ciao demonstrated the effectiveness of the proposed framework. Further experiments were conducted to understand the importance of interaction behaviors and homophily effect in building trust networks.

关键词： Trust network Sparse learning Homophily effect Interaction behaviors

来源：评论

学校读者我要写书评

暂无评论

Research on DDoS Attack Detection in Software Defined Network

Research on DDoS Attack Detection in Software Defined Networ...

引用

201. International Conference on Cloud Computing, Big Data and Blockchain, ICCBB 201.

作者： Zhao-Hui, Ma Gan-Sen, Zhao Wei-Wen, Li Ze-Feng, Mo Xin-Ming, Wang Bing-Chuan, Chen Cheng-Chuang, Lin School of Computer Science South China Normal University Guangzhou510631 China School of Information Science and Technology Guangdong University of Foreign Studies Guangzhou510006 China School of Mathematical Sciences South China Normal University Guangzhou510631 China School of Statistics and Mathematics Guangdong University of Finance and Economics Guangzhou510320 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun130012 China

ISBN: (纸本)9781538622803

Software Defined Network (SDN) is a new network construction. But due to its construction, SDN is vulnerable to be attacked by Distributed Denial of Service (DDoS) attack. So it is important to detect DDoS attack in SDN network. This paper presents a DDoS detection scheme based on k-means algorithm in SDN environment. The establishment of this scheme is based on the two hypotheses that the daily network works normally most of the time, and there is a significant difference between the data characteristics of normal situation and abnormal situation. At the same time, these two hypotheses are also true to the daily network condition. After demonstrating the validity of k-means clustering algorithm, the paper proposes 5 flow table features that can be used to detect DDoS attacks. Finally, the DDoS detection scheme was tested by simulation experiment. The test results showed that the method proposed by the author could effectively detect DDoS, with an average success rate of 97.78%. © 201. IEEE.

关键词： Denial-of-service attack

来源：评论

学校读者我要写书评

暂无评论

A novel Bayesian network-based fault prognostic method for semiconductor manufacturing process

A novel Bayesian network-based fault prognostic method for s...

引用

201. IEEE International Conference on Industrial Technology, ICIT 201.

作者： Wang, Guodong Hasani, Ramin M. Zhu, Yungang Grosu, Radu Institute of Computer Engineering Vienna University of Technology Austria College of Computer Science and Technology Jilin University China State Key Laboratory of Applied Optics Chinese Academy of Sciences China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University China

ISBN: (纸本)9781509053209

Fault prognostic in various levels of production of semiconductor chips is considered to be a great challenge. To reduce yield loss during the manufacturing process, tool abnormalities should be detected as early as possible during process monitoring. In this paper, we propose a novel fault prognostic method based on Bayesian networks. The network is designed such that it can process both discrete and continuous variables, to represent the correlations between critical deviations and to process quality control data based on divide-and-conquer strategy. Such a network enables us to perform high-precision multi-step prognostic on the status of the fabrication process given the current state of the sensory info. Additionally, we introduce a layer-wise approach for efficient learning of the Bayesian-network parameters. We evaluate the accuracy of our prognostic model on a wafer fabrication dataset where our model performs precise next-step fault prognostic by using the control sensory data. © 201. IEEE.

关键词： Bayesian networks

来源：评论

学校读者我要写书评

暂无评论

Multi-objective optimization for distributed collaborative beamforming in mobile wireless sensor networks

Multi-objective optimization for distributed collaborative b...

引用

IEEE Symposium on Computers and Communications

作者： Geng Sun Yanheng Liu Guojun Shen Aimin Wang Ying Zhang Victor C. M. Leung School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China College of Computer Science and Technology Jilin University Changchun China Department of Electrical and Computer Engineering University of British Columbia Vancouver BC Canada

Mobile wireless sensor networks (MWSN) are resource constrained, and have limited energy and transmission range. Distributed collaborative beamforming (DCB) in MWSN based on a virtual node antenna array (VNAA) can increase the transmission distance and enhance energy efficiency of a single sensor node. To achieve a lower maximum sidelobe level (SLL), sensor nodes can move to optimal locations with optimal excitation currents for DCB. However, this leads to an extra motion energy consumption. In this paper, we construct a multi-objective optimization framework to jointly optimize the maximum SLL, the transmission power and the motion energy consumption of the DCB nodes in MWSN. Moreover, an improved non-dorminated sorting genetic algorithm-II (INSGA-II) is proposed for solving the optimization problem. Simulation results show that the maximum SLL, the transmission power and the motion energy consumption of the VNAA can be effectively optimized by the proposed algorithms.

关键词： Mobile wireless sensor networks Collaborative beamforming Antenna arrays Genetic algorithm

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：