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作者： Chen, Hui-Ling Liu, Da-You Yang, Bo Liu, Jie Wang, Gang Wang, Su-Jing Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun 130012 China

ISBN: (纸本)9783642208409

This study proposes an efficient non-parametric classifier for bankruptcy prediction using an adaptive fuzzy k-nearest neighbor (FKNN) method, where the nearest neighbor k and the fuzzy strength parameter m are adaptively specified by the particle swarm optimization (PSO) approach. In addition to performing the parameter optimization for FKNN, PSO is utilized to choose the most discriminative subset of features for prediction as well. Time varying acceleration coefficients (TVAC) and inertia weight (TVIW) are employed to efficiently control the local and global search ability of PSO. Moreover, both the continuous and binary PSO are implemented in parallel on a multi-core platform. The resultant bankruptcy prediction model, named PTVPSO-FKNN, is compared with three classification methods on a real-world case. The obtained results clearly confirm the superiority of the developed model as compared to the other three methods in terms of Classification accuracy, Type I error, Type II error and AUC (area under the receiver operating characteristic (ROC) curve) criterion. It is also observed that the PTVPSO-FKNN is a powerful feature selection tool which has indentified a subset of best discriminative features. Additionally, the proposed model has gained a great deal of efficiency in terms of CPU time owing to the parallel implementation. © 2011 Springer-Verlag.

关键词： Particle swarm optimization (PSO)

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Heterogeneous data mining for planning active surveillance of malaria 15

Heterogeneous data mining for planning active surveillance o...

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ASE BigData and SocialInformatics, ASE BD and SI 2015

作者： Gu, Xiao Chen, Hechang Yang, Bo College of Computer Science and Technology Jilin University China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education China

ISBN: (纸本)9781450337359

Malaria is one of the most serious diseases in the world, which is densely distributed in poverty and remote areas. In the prevention and control of malaria, active surveillance is more efficient than passive surveillance to discover the incidences timely and accurately. However, it is always faced with the challenge of how to allocate the limited sources, such as medical staff and medicine, appropriately so as to achieve a maximum infect. In this paper, we propose a novel method to characterize the spatiotemporal patterns of infection risk for active surveillance planning. Specifically, we propose a temporal heterogeneous diffusion network model to discover high risk areas timely, and a mixture optimization method to find high risk areas accurately. The validation on existing real-world data shows that our method outperforms the existing state-of-the-art both in terms of infection risk prediction and planning of active surveillance under different thresholds. © 2015 ACM.

关键词： Mixtures

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Relating brain structure images to personality characteristics using 3D convolution neural network

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CAAI Transactions on Intelligence Technology 2021年第3期6卷 338-346页

作者： Lixian Cao Yanchun Liang Wei Lv Kaechang Park Yasuhiro Miura Yuki Shinomiya Shinichi Yoshida Zhuhai Laboratory of Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education Zhuhai College of Jilin UniversityZhuhaiChina Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education College of Computer Science and TechnologyJilin UniversityChangchunChina School of Information&Research Institute Kochi University of TechnologyKochiJapan

The Keras deep learning framework is employed to study MRI brain data in a preliminary analysis of brain structure using a convolutional neural *** results obtained are matched with the content of personality *** Big Five personality traits provide easy differentiation for dividing personalities into different *** now,the highest accuracy obtained from the results of personality prediction from the analysis of brain structure is about 70%.Although there is still no effective evidence to prove a clear relationship between brain structure and personality,the obtained results could prove helpful in understanding the basic relationship between brain structure and personality characteristics.

关键词： convolution structure dividing

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A novel method to measure graph similarity 12

A novel method to measure graph similarity

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12th IEEE International Conference on E-Business engineering, ICEBE 2015

作者： Wang, Xu Ouyang, Jihong College of Computer Science and Technology Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China

ISBN: (纸本)9781467380027

A novel method to measure the graph similarity is proposed, where the labels, in-degrees, and out-degrees of the vertices in the graph are comprehensively considered in order to conquer the high complexity and information loss in the measurement process. In this proposal, the graph is decomposed into a generalized tree and its similarity can be measured by computing the cost of the node sequence triples in the generalized tree. The proposed method decreases the computational complexity to O(n2) in comparison with the other available graph similarity methods. An example is provided to illustrate that the method is feasible and effective. © 2015 IEEE.

关键词： Forestry

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A Novel Method for Prediction of Protein Domain Using Distance-Based Maximal Entropy

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Journal of Bionic engineering 2008年第3期5卷 215-223页

作者： Shu-xue Zou Yan-xin Huang Yan Wang Chun-guang Zhou Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education College of Computer Science and Technology Jilin University Changchun 130012 P. R. China

Detecting the boundaries of protein domains is an important and challenging task in both experimental and computational structural biology. In this paper, a promising method for detecting the domain structure of a protein from sequence information alone is presented. The method is based on analyzing multiple sequence alignments derived from a database search. Multiple measures are defined to quantify the domain information content of each position along the sequence. Then they are combined into a single predictor using support vector machine. What is more important, the domain detection is first taken as an imbal- anced data learning problem. A novel undersampling method is proposed on distance-based maximal entropy in the feature space of Support Vector Machine （SVM）. The overall precision is about 80%. Simulation results demonstrate that the method can help not only in predicting the complete 3D structure of a protein but also in the machine learning system on general im- balanced datasets.

关键词： protein domain boundary SVM imbalanced data learning distance-based maximal entropy

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Simulating the Folding Pathway of RNA Secondary Structure Using the Modified Ant Colony Algorithm

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Journal of Bionic engineering 2010年第4期7卷 382-389页

作者： Jun Yu~(1,2),Changhai Zhang~(1,2),Yuanning Liu~(1,2),Xin Li~(1,2) 1.College of Computer Science and Technology,Jilin University,Changchun 130012,P.R.China 2.key laboratory of symbolic computation and knowledge engineering (ministry of education,China) Jilin University,Changchun 130012,P.R.China [a] College of Computer Science Technology Jilin University Changchun 130012 P. R. China [b] Key Laboratory of Symbolic Computation Knowledge Engineering (Ministry of Education China) Jilin University Changchun 130012 P. R. China

A new method for simulating the folding pathway of RNA secondary structure using the modified ant colony algorithmis *** a given RNA sequence,the set of all possible stems is obtained and the energy of each stem iscalculated and stored at the initial ***,a more realistic formula is used to compute the energy ofmulti-branch loop in the following *** a folding pathway is simulated,including such processes as constructionof the heuristic information,the rule of initializing the pheromone,the mechanism of choosing the initial andnext stem and the strategy of updating the pheromone between two different *** by testing RNA sequences withknown secondary structures from the public databases,we analyze the experimental data to select appropriate values *** measure indexes show that our procedure is more consistent with phylogenetically proven structures thansoftware RNAstructure sometimes and more effective than the standard Genetic Algorithm.

关键词： RNA secondary structure folding pathway ant colony algorithm

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A pseudo label based dataless naive bayes algorithm for text classification with seed words 27

A pseudo label based dataless naive bayes algorithm for text...

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27th International Conference on computational Linguistics, COLING 2018

作者： Li, Ximing Yang, Bo College of Computer Science and Technology Jilin University China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education China

ISBN: (纸本)9781948087506

Traditional supervised text classifiers require a large number of manually labeled documents, which are often expensive to obtain. Recently, dataless text classification has attracted more attention, since it only requires very few seed words of categories that are much cheaper. In this paper, we develop a pseudo-label based dataless Naive Bayes (PL-DNB) classifier with seed words. We initialize pseudo-labels for each document using seed word occurrences, and employ the expectation maximization algorithm to train PL-DNB in a semi-supervised manner. The pseudo-labels are iteratively updated using a mixture of seed word occurrences and estimations of label posteriors. To avoid noisy pseudo-labels, we also consider the information of nearest neighboring documents in the pseudo-label update step, i.e., preserving local neighborhood structure of documents. We empirically show that PL-DNB outperforms traditional dataless text classification algorithms with seed words. Especially, PL-DNB performs well on the imbalanced dataset. © 2018 COLING 2018 - 27th International Conference on computational Linguistics, Proceedings. All rights reserved.

关键词： Iterative methods

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Interval-valued fuzzy description logic IFALCN - Preliminary results

Interval-valued fuzzy description logic IFALCN - Preliminary...

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2010 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2010

作者： Huo, Linlin Ouyang, Jihong Liu, Dayou Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education College of Computer Science and Technology Jilin University Changchun China

ISBN: (纸本)9781424465835

To represent and reason with interval-value information of applications in description logic, based on interval-fuzzy set the classical des cription logic ALCN is extended to the fuzzy description logic IFALCN. Its' syntax, semantics and fuzzy tableau algorithm are presented in detail. Our work enhances the expressiveness and reasoning ability of ALCN. IFALCN is the generalization of fuzzy ALCN based on single value and more expressive than the latter and can conform to human cognition better. ©2010 IEEE.

关键词： Fuzzy sets

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A conditioned secure access control model based on multi-weighted roles in workflow system

A conditioned secure access control model based on multi-wei...

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5th International Conference on Control and Automation, ICCA'05

作者： Zhang, Jian Sun, Jigui Li, Niya Hu, Chengquan College of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University China

ISBN: (纸本)0780391381

The traditional RBAC model already cannot express the complicated secure access control constraint of the workflow. Based on the traditional RBAC model, a new conditioned RBAC model named as CMWRBSAC is proposed on the basis of multi-weighted roles. A conditioned RBAC strategy is discussed on the basis of dynamic role assignment. A new concept of workflow access authorization is defined on the basis of roles with multi-weights, including the hierarchy weight, the degree weight and the sequence weight. Furthermore, in order to solve the problems of the sequence constraint of cooperative activating task by multi-roles and multi-users, a sort algorithm based on token and a sort algorithm based on weighted roles synthesis are presented respectively. Finally, an example is given to show the work processes of these algorithms. This model can express complicated workflow secure access control constraint. © 2005 IEEE.

关键词： Security systems

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A globally optimal approach for surveillance video cropping

A globally optimal approach for surveillance video cropping

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作者： Liu, Jin Shi, Xiaohu Zhang, Yu College of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education 130012 Changchun China

In this paper, a novel approach for surveillance video cropping is presented. The basic idea is to obtain a trajectory that a small sub-window can take through the video, selecting the most important regions of the video for display on a smaller monitor. In this framework, the video content is firstly modeled by whether image frames change at each pixel. Then a shortest path algorithm is used to find the globally optimal trajectory for a cropping window. After that a second shortest path formulation is employed to find good cuts from one trajectory to another, improving the coverage of interesting events in the video content. Finally, additional techniques are demonstrated to improve the quality and efficiency of the algorithm, and results are shown on surveillance videos from PETS 2006.

关键词： Trajectories

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