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A method for translating belief function models to probability models

Journal of information and Computational Science 2011年第10期8卷 1817-1823页

作者： Xu, Peida Wu, Jiyi Li, Ya Cong, Jiang Sun, Xiaohong Kang, Bingyi Deng, Yong School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai 200240 China Hangzhou Key Laboratory of E-Business and Information Security Hangzhou Normal University Zhejiang 310036 China College of Food Science and Technology Shanghai Ocean University Shanghai 201306 China Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Hunan 411105 China Key Subject Laboratory of National defense for Radioactive Waste and Environmental Security Southwest University of Science and Technology Mianyang 621010 China College of Computer and Information Sciences Southwest University Chongqing 400715 China

One of the key issues in the applications of Dempster-Shafer evidence theory is how to make a decision based on Basic Probability Assignment (BPA). The conventional method is Pignistic Probability Transformation (PPT), which transforms BPA to probability distribution with equally assignment. To solve the existing problems of pignistic probability transformation, a new transformation method using an optimization algorithm based on the conflict coefficient k is proposed in this paper. The obtained probability has the minimum conflict coefficient with the original BPA. Numerical examples are used to illustrate the efficiency of the proposed method. © 2011 by Binary information Press.

关键词： Decision making

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imiRTP: An Integrated Method to Identifying miRNA-target Interactions in Arabidopsis thaliana

imiRTP: An Integrated Method to Identifying miRNA-target Int...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Jiandong Ding Shusi Yu Uwe Ohler Jihong Guan Shuigeng Zhou Shanghai Key Laboratory of Intelligent Information Processing and School of Computer Science Fudan University Shanghai China Institute for Genome Sciences & Policy and Department of Biostatistics & Bioinformatics Duke University Durham NC USA Department of Computer Science & Technology Tongji University Shanghai China

MiRNA are about 22nt long small noncoding RNAs that post transcriptionally regulate gene expression in animals, plants and protozoa. Confident identification of MiRNA-Target Interactions (MTI) is vital to understand their function. Currently, several integrated programs and databases are available for animal miRNAs, the mechanisms of which are significantly different from plant miRNAs. Here we present imiRTP, an integrated MTI prediction and analysis toolkit for Arabidopsis thaliana. It features two important functions: (i) combination of several effective plant miRNA target prediction methods provides a sufficiently large MTI candidate set, and (ii) different filters allow for an efficient selection of potential targets. The modularity of imiRTP enables the prediction of high quality targets on genome-wide scale.

关键词： Bioinformatics RNA Animals Genomics Databases Prediction methods Educational institutions

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An improved neural architecture for gaze movement control in target searching

An improved neural architecture for gaze movement control in...

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International Joint Conference on Neural Networks (IJCNN)

作者： Jun Miao Lijuan Duan Laiyun Qing Yuanhua Qiao Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences (CAS) Beijing China College of Computer Science and Technology Beijing University of Technology Beijing China School of Information Science and Engineering Graduate University of Chinese Academy of Sciences Beijing China College of Applied Science Beijing University of Technology Beijing China

This paper presents an improved neural architecture for gaze movement control in target searching. Compared with the four-layer neural structure proposed in [14], a new movement coding neuron layer is inserted between the third layer and the fourth layer in previous structure for finer gaze motion estimation and control. The disadvantage of the previous structure is that all the large responding neurons in the third layer were involved in gaze motion synthesis by transmitting weighted responses to the movement control neurons in the fourth layer. However, these large responding neurons may produce different groups of movement estimation. To discriminate and group these neurons' movement estimation in terms of grouped connection weights form them to the movement control neurons in the fourth layer is necessary. Adding a new neuron layer between the third layer and the fourth lay is the measure that we solve this problem. Comparing experiments on target locating showed that the new architecture made the significant improvement.

关键词： Neurons Visualization Image coding Encoding Context Feature extraction Equations

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Adaptive discriminant analysis for face recognition from single sample per person

Adaptive discriminant analysis for face recognition from sin...

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International Conference on Automatic Face and Gesture Recognition

作者： Meina Kan Shiguang Shan Yu Su Xilin Chen Wen Gao Key Laboratory of Intelligent Information Processing Chinese Academy and Sciences Beijing China Chinese Academy of Sciences Beijing Beijing CN Department of Computer Science University of Caen France Institute of Digital Media Peking University Beijing China School of Computer Science and Technology Harbin Institute of Technology Beijing China

Discriminant analysis, especially Fisherface and its numerous variants, have achieved great success in face recognition. However, these methods fail to work for face recognition from Single Sample per Person (SSPP), since they need more than one sample per person to estimate the within-class scatter matrix. To break this inability of traditional discriminant analysis, our paper proposes Adaptive Discriminant Analysis (ADA). In our method, the within-class scatter matrix of each enrolled subject is estimated from his/her single sample, by inferring from a generic training set with multiple samples per person. The inference is inspired by a simple intuition that similar person follows similar within-class variations. Specifically, both kNN regression and Lasso regression are explored for this purpose. We evaluate our method on FERET database and a large real-world face database. The results are very impressive compared with dominant traditional solutions to SSPP problem.

关键词： Training Databases Face Face recognition Testing Lighting Nearest neighbor searches

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A more effective definition of evidential conflict combined with evidential distance

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Journal of information and Computational Science 2011年第9期8卷 1729-1734页

作者： Chen, Yuxin Wu, Jiyi Cong, Jian Jie, Wenjing Deng, Yong School of Electronics and Information Technology Shanghai Jiao Tong University Shanghai 20024 China Hangzhou Key Lab of E-Business and Information Security Hangzhou Normal University Hangzhou 310036 China College of Food Science and Technology Shanghai Ocean University 999 Hucheng Huan Road Shanghai 201306 China Key Subject Laboratory of National Defense for Radioactive Waste and Environment Security Southwest University of Science and Technology Mianyang 621010 China Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan Hunan 411105 China College of Computer and Information Sciences Southwest University Chongqing 400715 China

Evidence theory is widely used in many application systems such as information fusion and decision making under uncertainty environment. However, the classical Dempster combination rule is not efficient to deal with highly conflicting evidences. One of the open issues is how to determine the conflict degree in conflict evidence management. In this paper, a new conflict coefficient is proposed to measure the conflict degree between bodies of evidence. It can overcome some drawbacks of the classical conflict coefficient. The numerical example shows the efficiency of our proposed method. Copyright © 2011 Binary information Press.

关键词： information fusion

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Optimal aggregation of interval numbers based on genetic algorithm in group decision

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Journal of information and Computational Science 2011年第5期8卷 842-849页

作者： Kang, Bingyi Zhang, Yajuan Deng, Xinyang Wu, Jiyi Sun, Xiaohong Li, Ya Deng, Yong College of Computer and Information Sciences Southwest University Chongqing 400715 China Hangzhou Key Lab of E-Business and Information Security Hangzhou Normal University Hangzhou 310036 China College of Food Science and Technology Shanghai Ocean University 999 Hucheng Huan Road Shanghai 201306 China Key Subject Laboratory of National Defense for Radioactive Waste and Environmental Security Southwest University of Science and Technology Mianyang 621010 China Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan Hunan 411105 China School of Electronics and Information Technology Shanghai Jiaotong University Shanghai 200240 China

A group of decision-makers may differ in their choice of alternatives while making a decision. As a result, how to aggregate opinions of different experts is still an open issue. Due to the uncertainty in the process of decision making, some mathematic tools such as fuzzy sets theory and evidence theory, are used to model uncertain information. In this paper, the experts' opinions are represented by interval numbers. A new optimal aggregation method to combine interval data is proposed based on genetic algorithm. The new method can deal with experts' opinions in an efficient manner. A numerical example on group decision making under uncertain environment is used to illustrate the efficiency of our proposed method. Copyright © 2011 Binary information Press.

关键词： Genetic algorithms

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Sparsely Encoded Local Descriptor for face recognition

Sparsely Encoded Local Descriptor for face recognition

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International Conference on Automatic Face and Gesture Recognition

作者： Zhen Cui Shiguang Shan Xilin Chen Lei Zhang School of Computer Science and Technology Huaqiao University Xiamen China Chinese Academy and Sciences Beijing China Key Laboratory of Intelligent Information Processing Institute of Computer Technology Chinese Academy and Sciences Beijing China Chinese Academy of Sciences Beijing Beijing CN Department of Computing Hong Kong Polytechnic University Hong Kong China

In this paper, a novel Sparsely Encoded Local Descriptor (SELD) is proposed for face recognition. Compared with K-means or Random-projection tree based previous methods, sparsity constraint is introduced in our dictionary learning and sequent image encoding, which implies more stable and discriminative face representation. Sparse coding also leads to an image descriptor of summation of sparse coefficient vectors, which is quite different from existing code-words appearance frequency(/histogram)-based descriptors. Extensive experiments on both FERET and challenging LFW database show the effectiveness of the proposed SELD method. Especially on the LFW dataset, recognition accuracy comparable to the best known results is achieved.

关键词： Face Dictionaries Pixel Training Feature extraction Face recognition Databases

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Determination of relative significance factor of impact categories based on fuzzy multiattribute decision-making method

Determination of relative significance factor of impact cate...

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Chinese Control and Decision Conference, CCDC

作者： Xinyang Deng Yajuan Zhang Bingyi Kang Jiyi Wu Xiaohong Sun Yong Deng School of Computer and Information Sciences Southwest University Chongqing China Hangzhou Key Laboratory of E-Business and Information Security Hangzhou Normal University Hangzhou Zhejiang China College of Food Science and Technology Shanghai Ocean University Shanghai China Laboratory of Intelligent Computing & Information Processing of Ministry of Education Xiangtan University Xiangtan Hunan China School of Electronics & Information Technology Shanghai Jiaotong University Shanghai China Laboratory of National defense for Radioactive Waste and Environmental Security Southwest University of Science and Technology Mianyang China

A relative significance factor of an impact category is the external weight of the impact category and plays an important role in life cycle assessment(LCA). Many multiattribute decision-making (MADM) methods such as analytical hierarchy process(AHP), the rank-order centroid method and the fuzzy method are proposed to determine the relative significance factor of an impact category. However, in previous research, it is shown that, the AHP approach is difficult for experts rendering consistent judgment when the number of pairwise comparisons increases, the rank-order method has some insurmountable shortcomings, the key issue to use fuzzy set theory is its complexity. In order to address this problem, a new simple and efficient method is proposed to determine relative significance factor in a more efficient manner. An example to determine relative significance factor of impact categories is shown to illustrate the efficiency of the proposed method.

关键词： Decision making Educational institutions Complexity theory Pragmatics Uncertainty Fuzzy set theory Fuzzy sets

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An improved radius of gyration similarity measure between generalized fuzzy numbers and its application to multisource data fusion

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Journal of computers 2011年第8期6卷 1732-1739页

作者： Yong, Deng Dong, Sun Wen, Jiang Jianling, Xu College of computer and information sciences Southwest University Chongqing 400715 China Hangzhou Key Lab of E-Business and Information Security Hangzhou Normal University Hanzhou Zhejiang 310036 China School of Electronics and Information Technology Shanghai Jiao Tong University Shanghai 200240 China Key Laboratory of Intelligent Computing Information Processing of Ministry of Education Xiangtan University Xiangtan Hunan 411105 China Department of Electronics Engineering Northwestern Polytechnical University Xían 710072 China Grain Economics Institute Nanjing University of Finance and Economics Nanjing 210003 China

The degree of similarity between fuzzy numbers plays an important role in fuzzy information fusion. In this paper, improved ROG-based similarity measure developed from the current ROG method is presented. It is shown that the new method can overcome some shortcomings of the existing similarity measures. Based on the proposed similarity measure, a more flexible and intelligent algorithm is developed to deal with multisensor data fusion problems. A numerical example is used to illustrate the efficiency of the proposed method. © 2011 ACADEMY PUBLISHER.

关键词： Numerical methods

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Concept lattice mining algorithm using rough entropy with variable precision thresholding and co-evolution

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Jiefangjun Ligong Daxue Xuebao/Journal of PLA University of Science and technology (Natural Science Edition) 2011年第1期12卷 25-30页

作者： Ding, Wei-Ping Wang, Jian-Dong Guan, Zhi-Jin College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing 210016 China School of Computer Science and Technology Nantong University Nantong 226019 China Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou 215006 China

Based on some special advantages of variable precision rough sets model and co-evolutionary particle swarm algorithm, a novel concept lattice mining algorithm (REVPT)using rough entropy with variable precision thresholding and co-evolution was proposed to solve some optimization problems of the concept lattice mining. In this algorithm, variable precision rough entropy was used to scale the subpopulations of various concept lattices dynamically, and rough approximation lattices constructed. The global optimization efficiency of concept lattices was improved by sharing search experiences among different populations, which can reduce the scale of the former concept lattices, and deduce the consistent decision rule sets efficiently. The experimental results show that the proposed algorithm is better on the convergence and lattice optimization when the variable precision thresholding β is at a certain appropriate range. Therefore it is of robustness on the rules mining accuracy and efficiency.

关键词： Global optimization

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