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Adaptive social network construction using Gaussian mixture model

Information Technology Journal 2011年第12期10卷 2252-2259页

作者： Guo, Xin Xiang, Yang Chen, Qian Wei, Wei Department of Computer Science and Technology School of Electronic and Information Engineering Tongji University Shanghai 201804 China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 200092 China

A Social network graph shows social interactions and relationships between individuals in a specific social environment, which is very helpful for analyzing social relationships, activities, structures, etc. The author quantized the strengths of social objects' relationships in social environment using an improved vector space model. Gaussian mixture model was employed to set the threshold for identifying social relationships adaptively and divide social subgroups automatically. According to the threshold, social network graph would be constructed based on performance measures. It is concluded that hidden social relationships can be discovered effectively by using this approach which is very flexible and adaptive for dynamic information feedback mechanism. © 2011 Asian Network for Scientific Information.

关键词： Gaussian distribution

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A hierarchical clustering strategy of processing class imbalance and its application in fraud detection 21

A hierarchical clustering strategy of processing class imbal...

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21st IEEE International Conference on High Performance Computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on Data Science and systems, HPCC/SmartCity/DSS 2019

作者： Zhang, Youjun Liu, Guanjun Zheng, Lutao Yan, Chungang Key Laboratory of the Ministry of Education for Embedded System and Service Computing Shanghai Electronic Transactions and Information Service Collaborative Innovation Center Tongji University Shanghai China

ISBN: (纸本)9781728120584

With the Internet and mobile communications becoming an indispensable part of people's daily lives, online transactions have become one of the most common payment methods. However, transaction fraud incidents also occur frequently, causing a larger number of economic losses. Therefore, transaction fraud detection is significant. The methods of machine learning are often used to detect fraudulent transactions from a larger amount of transaction data. However, the class imbalance problem reduces the performance of these methods. There are mainly four factors causing this problem: imbalanced class distribution, sample size, class separability and within-class concept. The existing improvement strategies for class imbalance mainly focus on the first factor but omit other three ones. This paper considers the four factors to propose a comprehensive model called clustering tree. Constructing a clustering tree includes two steps: 1) we first select a clustering algorithm considering the class separability;and then 2) we use this clustering algorithm to construct a tree that can be used to determine if an incoming transaction is illegal. The root node of this tree contains all samples, and we consider both the imbalanced class distribution and the within-class concept when samples are hierarchically divided into sub-nodes during the constructing process. We compare the proposed method with five state-of-the-art ones on two real transaction datasets, and the experimental results show that our method works better. © 2019 IEEE.

关键词： Clustering algorithms

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Probabilistic bootstrap-based evolutionary algorithm for three-objective wind farm turbine position optimization

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Swarm and Evolutionary Computation 2025年 96卷

作者： Chen Zhang Haotian Li Xiuxian Li Jiujun Cheng Zhenyu Lei Shangce Gao Faculty of Engineering University of Toyama Toyama-shi 930-8555 Japan College of Electronics and Information Engineering Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai China Ministry of Education Key Laboratory of Embedded System and Service Computing Tongji University Shanghai China

Amid the worsening energy crisis, wind farm layout optimization (WFLO) to increase power generation, reduce costs, and mitigate potential environmental impacts is of great significance. This paper formulates three-objective wind farm layout optimization (TWFLO) which is rarely considered, aiming to effectively utilize existing information to optimize power output, land usage, and costs. We propose a new algorithm (MOEA/D-P) based on probability distributions to guide turbine placement and improve the performance of a Multiobjective Evolutionary Algorithm Based on Decomposition (MOEA/D). This algorithm addresses the issue of neglecting valuable information during layout optimization. Additionally, we make improvements to the traditional land-use function to avoid situations where non-convex layouts result in an area calculation of zero. The MOEA/D-P is tested on six different initial layouts and compared with five algorithms under two wind conditions. Results are evaluated using inverted generational distance, hypervolume, and scatter plot distributions. The impact of initial probability distribution on algorithm performance is discussed under four simple wind conditions. The results show that MOEA/D-P outperforms the other five algorithms in terms of performance.

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A Novel Mutual Information based Ant Colony Classifier 5

A Novel Mutual Information based Ant Colony Classifier

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2017 International Conference on Progress in Informatics and Computing(PIC)

作者： Hang Yu Xiaoxiao Qian Yang Yu Jiujun Cheng Ying Yu Shangce Gao College of Computer Science and Technology Taizhou University Faculty of Engineering University of Toyama Key Laboratory of Embedded System and Service Computing Ministry of EducationTongji University

ISBN: (纸本)9781538619797;9781538619780

By constructing a list of IF-THEN rules, the traditional ant colony optimization(ACO) has been successfully applied on data classification with not only a promising accuracy but also a user comprehensibility. However, as the collected data to be classified usually contain large volumes and redundant features, it is challenging to further improve the classification accuracy and meanwhile reduce the computational time for *** paper proposes a novel hybrid mutual information based ant colony algorithm(mrAM+) for classification. First, a maximum relevance minimum redundancy feature selection method is used to select the most informative and discriminative attributes in a dataset. Then, we use the enhanced ACO classifier(i.e., AM+)to perform the classification. Experimental results show that the proposed mrAM+ outperforms other seven state-of-art related classification algorithms in terms of accuracy and the size of model.

关键词： ant colony optimization mutual information classification data mining feature selection

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Upper Bounds on Lifetime of Three Dimensional Extended UWB Sensor Networks

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电子学报(英文版) 2010年第2期19卷 307-312页

作者： XU Juan JIANG Changjun GUO Aihuang HONG Yongfa LI Shu WANG Cheng School of Electronics and Information Engineering Tongji University Shanghai China Key Laboratory of Embedded System and Service Computing of the Ministry of Education Tongji University Shanghai China College of Information Science and Engineering Shandong University of Science and Technology Qingdao China

The upper bounds on lifetime of three dimensional extended Time hopping impulse radio Ultrawide band (TH-IR UWB) sensor networks are derived using percolation theory arguments. The TH-IR UWB sensor network consists of n sensor nodes distributed in a cube of edge length n^1/3 according to a Poisson point process of unit intensity. It is shown that for such a static three dimensional extended TH-IR UWB sensor network, the upper bound on the lifetime is of order O(n^-1), while in the ideal case, the upper bound on the lifetime is longer than that of a static network by a factor of n ^2/3. Therefore sensor nodes moving randomly in the deployment area can improve the upper bound on network lifetime. The results also reveal that the upper bounds on network lifetime decrease with the number of nodes n, thus extended THIR UWB sensor networks aren't prone to be employed in large-scale network.

关键词：无线传感器网络三维扩展寿命延长超宽带上界静态网络生存时间移动节点

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Performance analysis for large scale parallel microscopic traffic simulation system

Performance analysis for large scale parallel microscopic tr...

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International Symposium on Advances in Computer and Sensor Networks and systems, 2008

作者： Fei, Yin Dongliang, Zhang Department of Computer Science and Technology Tongji University The Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai 201804 China

ISBN: (纸本)9781427629807

In this paper, we present the parallel implementation of the traffic microsimulation PMTS (Parallel Microscopic Traffic Simulation) focusing on the performance issues. The parallelization of PMTS is domain decomposition, which means that each processor of the PC cluster is responsible for a different geographical area of the simulation region. We describe the transportation network graph partition and information exchange between domains. We demonstrate the time cost mathematics models for PMTS: the vehicle generation, vehicle position calculation, and vehicle information exchange between domains. The workload balance is obtained by adjusting the boundary lines according to the relative load of adjacent subnetworks. All these works have been proved to be effective when PMTS put into use and the experiment results are also provided which match our analysis.

关键词： Vehicles

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Robust Learning to Rank Based on Portfolio Theory and AMOSA Algorithm

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IEEE Transactions on systems, Man, and Cybernetics: systems 2017年第6期47卷 1007-1018页

作者： Li, Jinzhong Liu, Guanjun Yan, Chungang Jiang, Changjun Key Laboratory of the Ministry of Education for Embedded System and Service Computing Department of Computer Science and Technology Tongji University Shanghai201804 China Key Laboratory of Watershed Ecology and Geographical Environment Monitoring NASG Department of Computer Science and Technology Jinggangshan University Ji'an343009 China

Effectiveness is the most important factor considered in the ranking models yielded by algorithms of learning to rank (LTR). Most of the related ranking models only focus on improving the average effectiveness but ignore robustness. When a ranking model ignores robustness, the effectiveness for many queries is possibly very poor although the average effectiveness for all queries is relatively high. Therefore, Wang et al. first consider robustness in their ranking models. However, the robustness formula defined by Wang et al. cannot characterize those queries whose effectiveness are hurt seriously in comparison with the baseline model. In order to overcome this shortcoming, we propose a novel formula of characterizing robustness based on portfolio theory, and construct a multiobjective optimization model of the robust LTR in which the formula is used. Based on this model, we propose an approach of risk-sensitive and robust LTR, named as R2Rank, which is based on the framework of archived multiobjective simulated annealing algorithm and the idea of preference ranking organization method for enrichment evaluation. The experimental results show that the ranking models produced by our proposed R2Rank approach are better in both effectiveness and robustness than those produced by three state-of-the-art LTR approaches. © 2016 IEEE.

关键词： Simulated annealing

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Fuzzy H∞ Filtering for Nonlinear Networked systems with Multiple Stochastic Time-Varying Delays, Packet Dropouts and Sensor Saturation 34

Fuzzy H∞ Filtering for Nonlinear Networked Systems with Mul...

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第三十四届中国控制会议

作者： XU Xiaoli YAN Huaicheng ZHANG Hao SHI Hongbo Key Laboratory of Advanced Control and Optimization for Chemical Process of Ministry of Education School of information Science and Engineering East China University of Science and Technology Key Laboratory of Embedded System and Service Computing Ministry of Education

ISBN: (纸本)9781467374439

This paper investigates the problem of H∞ filter design for a class of nonlinear networked system based on T-S fuzzy model. Multiple stochastic time-varying delays and some incomplete information are considered simultaneously. Incomplete information includes randomly occurring sensor saturation and packet dropouts. Stochastic time-varying delays are depicted as a sequence of stochastic and independent variables, which take values on 0 and 1. Two sets of Bernoulli distributed white noises are introduced to describe randomly occurring sensor saturation and packet dropouts. system conservatism is reduced due to introduce an approach of piecewise quadratic Lyapunov function. By solving a set of linear matrix inequalities(LMIs), the filter parameters are obtained. Finally, a simulation example is provided to illustrate the effectiveness of the proposed filter design approach.

关键词： H ∞ filtering,multiple time-varying delays,randomly occurring sensor saturation,packet dropouts,piecewise quadratic Lyapunov function

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Large-scale video compression： recent advances and challenges

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Frontiers of Computer Science 2018年第5期12卷 825-839页

作者： Tao TIAN Hanli WANG Department of Computer Science and Technology Tongji University Shanghai 201804 China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 200092 China Shanghai Engineering Research Center of Industrial Vision Perception & Intelligent Computing Shanghai 200092 China

The evolution of social network and multimedia technologies encourage more and more people to generate and upload visual information, which leads to the generation of large-scale video data. Therefore, preeminent compression technologies are highly desired to facilitate the storage and transmission of these tremendous video data for a wide variety of applications. In this paper, a systematic review of the recent advances for large-scale video compression （LSVC） is presented. Specifically, fast video coding algorithms and effective models to improve video compression efficiency are introduced in detail, since coding complexity and compression efficiency are two important factors to evaluate video coding approaches. Finally, the challenges and fu- ture research trends for LSVC are discussed.

关键词： large-scale video compression fast video coding compression efficiency

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Utilizing adaptive techniques to supress noise in high frequency ground wave radar

Utilizing adaptive techniques to supress noise in high frequ...

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4th Microwave and Radar Week MRW-2010 - 11th International Radar Symposium, IRS 2010

作者： Gui, Renzhou Key Laboratory of Embedded System and Service Computing Ministry of Education College of Electronics and Information Engineering Tongji University Shanghai 200092 China State Key Laboratory of Millimeter Waves China

ISBN: (纸本)9789955690184

Reducing noise disturbances in the frequency segment of high frequency (HF) ground wave radar and restraining the sidelobes of strong targets that interfere with the detection of weak targets are the interesting Topic. A new method based on an adaptive techniques that solves these problems is proposed. By changing the working time of the frequency spectrum monitor (FSM), we have shown not only that radar can run in the frequency segments with lower noise disturbances, but also that the noise data produced by FSM can be exploited effectively. There is no correlation between the noise and the useful echo signal, though the correlation between noises over very short time periods is strong,. Exploiting the phenomena, we can adjust system parameters in real-time by adaptive methods to solve the two problems,namely sidelobe disturbance of strong targets and noise distrubance in the frequency segment.

关键词： Bandpass filters

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