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Cartesian product over interval valued intuitionistic fuzzy sets

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Journal of Systems Engineering and Electronics 2017年第6期28卷 1152-1161页

作者： Jianming Xie sanyang liu School of Mathematics and Statistics Xidian University Xi’an 710071 China

The intuitionistic fuzzy set(IFS) based on fuzzy theory,which is of high efficiency to solve the fuzzy problem, has been introduced by Atanassov. Subsequently, he pushed the research one step further from the IFS to the interval valued intuitionistic fuzzy set(IVIFS). On the basis of fuzzy set(FS), the IFS is a generalization concept. And the IFS is generalized to the *** this paper, the definition of the sixth Cartesian product over IVIFSs is first introduced and its some properties are *** prove some equalities based on the operation and the relation over IVIFSs. Finally, we present one geometric interpretation and a numerical example of the sixth Cartesian product over IVIFSs.

关键词： intuitionistic fuzzy sets(IFS) Cartesian product ope ration geometric interpretation interval valued intuitionistic fuzzy set(IVIFS)

Progressive transductive learning pattern classification via single sphere

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Journal of Systems Engineering and Electronics 2009年第3期20卷 643-650页

作者： Xue Zhenxia liu sanyang liu Wanli Dept. of Applied Mathematics Xidian Univ. Xi'an 710071 P. R. China Dept. of Mathematics Henan Univ. of Science and Technology Luoyang 471003 P. R. China Dept. of Mathematics Luoyang Normal Coll. Luoyang 471022 P. R. China

In many machine learning problems, a large amount of data is available but only a few of them can be labeled easily. This provides a research branch to effectively combine unlabeled and labeled data to infer the labels of unlabeled ones, that is, to develop transductive learning. In this article, based on Pattern classification via single sphere （SSPC）, which seeks a hypersphere to separate data with the maximum separation ratio, a progressive transductive pattern classification method via single sphere （PTSSPC） is proposed to construct the classifier using both the labeled and unlabeled data. PTSSPC utilize the additional information of the unlabeled samples and obtain better classification performance than SSPC when insufficient labeled data information is available. Experiment results show the algorithm can yields better performance.

关键词： pattern recognition semi-supervised learning transductive learning classification support vector machine support vector domain description.

Hooke and Jeeves algorithm for linear support vector machine

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Journal of Systems Engineering and Electronics 2010年第1期21卷 138-141页

作者： Yeqing liu sanyang liu Mingtao Gu Department of Mathematical Sciences Xidian University Xi'an 710071 R R. China School of Science Henan University of Science & Technology Luoyang 471003 P. R. China PLA Unit 96251 Luoyang 471003 E R. China

Coordinate descent method is a unconstrained optimization technique. When it is applied to support vector machine （SVM）, at each step the method updates one component of w by solving a one-variable sub-problem while fixing other components. All components of w update after one iteration. Then go to next iteration. Though the method converges and converges fast in the beginning, it converges slow for final convergence. To improve the speed of final convergence of coordinate descent method, Hooke and Jeeves algorithm which adds pattern search after every iteration in coordinate descent method was applied to SVM and a global Newton algorithm was used to solve one-variable subproblems. We proved the convergence of the algorithm. Experimental results show Hooke and Jeeves＇ method does accelerate convergence specially for final convergence and achieves higher testing accuracy more quickly in classification.

关键词： support vector machine classification pattern search,Hooke and Jeeves coordinate descent global Newton algorithm.

Algorithm for multi-constrained path selection based on experimental analysis

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Journal of Systems Engineering and Electronics 2006年第4期17卷 931-937页

作者： Qi Xiaogang liu Lifang liu sanyang Dept. of Mathematics Science Xidian Univ. Xi'an 710071 P. R. China

It is a challenging problem to provide quality-of-service （QoS） guarantees in next generation high-speed network, and the QoS routing is one of the key issues of the problem. For the problem of multi-constrained QoS routing in high-speed network, especially under the inaccurate link state information, the success ratio of the different constraint combination is analyzed statistically, and a constraint analysis method based on the computer simulation is proposed. Furthermore, the approximately equal loose-tight order relation between each two constraints is constructed, and then an algorithm based on the experimental analysis is presented. Finally, the simulation result demonstrates that the algorithm has the higher success ratio, and the theoretical analysis proves its correctness and universality.

关键词： multi-constrained routing quality of service (QoS) path selection computer simulation experimental analysis

Clustering routing algorithm of wireless sensor networks based on Bayesian game

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Journal of Systems Engineering and Electronics 2012年第1期23卷 154-159页

作者： Gengzhong Zheng sanyang liu Xiaogang Qi School of Computer Science and Technology Xidian University Xi＇an 710071 R R. China Department of Mathematics and Information Technology Hanshan Normal University Chaozhou 521041 R R. China School of Science Xidian University Xi＇an 710071 R R. China

To avoid uneven energy consuming in wireless sen- sor networks, a clustering routing model is proposed based on a Bayesian game. In the model, Harsanyi transformation is introduced to convert a static game of incomplete information to the static game of complete but imperfect information. In addition, the existence of Bayesian nash equilibrium is proved. A clustering routing algorithm is also designed according to the proposed model, both cluster head distribution and residual energy are considered in the design of the algorithm. Simulation results show that the algorithm can balance network load, save energy and prolong network lifetime effectively.

关键词： wireless sensor networks (WSNs) clustering routing Bayesian game energy efficiency.

Successive quadratic programming multiuser detector

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Journal of Systems Engineering and Electronics 2007年第1期18卷 8-13页

作者： Mu Xuewen Zhang Yaling liu sanyang Dept. of Applied Mathematics Xidian Univ. Xi'an 710071 E R. China Dept. of Computer Science and Technology Xi'an Univ. of Science and Technology Xi'an 710054 P. R. China

Based on the semidefinite programming relaxation of the CDMA maximum likelihood multiuser detection problem, a detection strategy by the successive quadratic programming algorithm is presented. Coupled with the randomized cut generation scheme, the suboptimal solution of the multiuser detection problem in obtained. Compared to the interior point methods previously reported based on semidefmite programming, simulations demonstrate that the successive quadratic programming algorithm often yields the similar BER performances of the multiuser detection problem. But the average CPU time of this approach is significantly reduced.

关键词： Code division multiple access Multiuser detection Semidefinite programming Successive quadratic programming.

Statistical Diagnosis for HIV Dynamics Based on Mean Shift Outlier Model

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Journal of Systems Science & Complexity 2015年第3期28卷 592-605页

作者： WU Ting liu sanyang ZHOU Jie School of Mathematics and Statistics Xidian University

Ordinary differential equation(ODE) are widely used for quantifying HIV viral *** is interesting but challenging to estimate ODE parameters from noisy data, especially when the data have some outliers. In this study, the authors use the Mean Shift Outlier Model(MSOM) to detect outliers in HIV model based on the two-step estimation of ODE. Approximate formula for shift parameter is derived. Furthermore, a score test statistic is constructed and its approximating distribution is established. The simulation results show that: 1) The boundary points have more impact on the parameter estimation relative to interior points. 2) The proposed procedure can detect the outliers effectively. The authors illustrate the proposed approach using an application example from an HIV clinical trial and find similar pattern to the simulation studies.

关键词： HIV dynamics local polynomial smoothing mean shift outlier model nonparametric regression.

Adjustable entropy function method for support vector machine

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Journal of Systems Engineering and Electronics 2008年第5期19卷 1029-1034页

作者： Wu Qing liu sanyang Zhang Leyou Dept. of Mathematical Sciences Xidian Univ. Xi'an 710071 P. R. China

Based on KKT complementary condition in optimization theory, an unconstrained non-differential optimization model for support vector machine is proposed. An adjustable entropy function method is given to deal with the proposed optimization problem and the Newton algorithm is used to figure out the optimal solution. The proposed method can find an optimal solution with a relatively small parameter p, which avoids the numerical overflow in the traditional entropy function methods. It is a new approach to solve support vector machine. The theoretical analysis and experimental results illustrate the feasibility and efficiency of the proposed algorithm.

关键词： optimization support vector machine adjustable entropy function Newton algorithm.

Using junction trees for structural learning of Bayesian networks

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Journal of Systems Engineering and Electronics 2012年第2期23卷 286-292页

作者： Mingmin Zhu sanyang liu Youlong Yang Kui liu Department of Mathematics Xidian UniversityXi'an 710071P.R.China

The learning Bayesian network （BN） structure from data is an NP-hard problem and still one of the most exciting chal- lenges in the machine learning. In this work, a novel algorithm is presented which combines ideas from local learning, constraint- based, and search-and-score techniques in a principled and ef- fective way. It first reconstructs the junction tree of a BN and then performs a K2-scoring greedy search to orientate the local edges in the cliques of junction tree. Theoretical and experimental results show the proposed algorithm is capable of handling networks with a large number of variables. Its comparison with the well-known K2 algorithm is also presented.

关键词： Bayesian network (BN) junction tree scoring function structural learning conditional independence.