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2012 International Conference on System Science and Engineering (ICSSE)最新文献

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Output-feedback adaptive DSC of stochastic nonlinear systems with time-delays 随机非线性时滞系统的输出反馈自适应DSC
2012 International Conference on System Science and Engineering (ICSSE) Pub Date : 2012-08-02 DOI: 10.1109/ICSSE.2012.6257186
Dongjuan Li, Jing Zhang, Yanjun Liu, N. Luo, Yang Cui, Lei Liu
{"title":"Output-feedback adaptive DSC of stochastic nonlinear systems with time-delays","authors":"Dongjuan Li, Jing Zhang, Yanjun Liu, N. Luo, Yang Cui, Lei Liu","doi":"10.1109/ICSSE.2012.6257186","DOIUrl":"https://doi.org/10.1109/ICSSE.2012.6257186","url":null,"abstract":"The dynamic surface control (DSC) technique can simplify the backstepping design for the control of nonlinear systems by overcoming the problem of “explosion of complexity”. In this paper, we incorporating this design technique into a neural network based adaptive control design framework for a class of nonlinear stochastic systems. The time delays exist in the systems and the neural networks are employed to compensate for all unknown nonlinear terms depending on the delayed output, and our development is able to eliminate the problem of “explosion of complexity” inherent in the existing method.","PeriodicalId":113116,"journal":{"name":"2012 International Conference on System Science and Engineering (ICSSE)","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127807099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Parallel processing the keyword search in uncertain environment 不确定环境下关键字搜索的并行处理
2012 International Conference on System Science and Engineering (ICSSE) Pub Date : 2012-08-02 DOI: 10.1109/ICSSE.2012.6257218
B. Ning, Xiaoping Zhou, Yimin Shi
{"title":"Parallel processing the keyword search in uncertain environment","authors":"B. Ning, Xiaoping Zhou, Yimin Shi","doi":"10.1109/ICSSE.2012.6257218","DOIUrl":"https://doi.org/10.1109/ICSSE.2012.6257218","url":null,"abstract":"XML is nature to express the uncertainty in real world, therefore the data in uncertain environment can be stored it the format of XML. For improving the efficiency of keyword search in uncertain environment, we use dewey code for indexing the XML elements, which is a kind of prefix-based encoding method. When dealing with big data, the lengths of element's Dewey codes are quit big, which leads to low efficiency of judging the relationships among the elements and needs large storage space. Thus, the big XML data and complicated XML schema are the bottlenecks of keyword search. In this paper, we incorporate the map-reduce mechanism to manage the uncertain data with partition, and design a parallel method to process information retrieve. The different XML fragments are stored in distributed network, and these can be parallel processed to retrieve the Smallest Lowest Common Ancestors (SLCAs) and return the k results with the largest probabilistic values. In our experiment, the result shows that our approach can improve the efficiency of executing parallel keyword search.","PeriodicalId":113116,"journal":{"name":"2012 International Conference on System Science and Engineering (ICSSE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121097129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Parallel attribute-weighted fuzzy c-means algorithm for clustering 并行属性加权模糊c均值聚类算法
2012 International Conference on System Science and Engineering (ICSSE) Pub Date : 2012-08-02 DOI: 10.1109/ICSSE.2012.6257156
Jin Zhou, C. L. P. Chen, Long Chen
{"title":"Parallel attribute-weighted fuzzy c-means algorithm for clustering","authors":"Jin Zhou, C. L. P. Chen, Long Chen","doi":"10.1109/ICSSE.2012.6257156","DOIUrl":"https://doi.org/10.1109/ICSSE.2012.6257156","url":null,"abstract":"Due to energy and bandwidth constraints, traditional data clustering approaches are challenging when the communication to a central processing unit is discouraged in Wireless Sensor Networks. In this paper, a new parallel attribute-weighted fuzzy c-means (PWFCM) algorithm is proposed, in which parallel clustering solution can be achieved by exchanging the centroid messages among single-hop neighbours only. At the same time, the important features can be extracted based on the attribute weight entropy regularization. Experiments on real and synthetic datasets have demonstrated the suitability and efficiency of the presented algorithm.","PeriodicalId":113116,"journal":{"name":"2012 International Conference on System Science and Engineering (ICSSE)","volume":"109 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123335525","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Research on evaluation of transfer efficiency of Rail transportation hub 轨道交通枢纽换乘效率评价研究
2012 International Conference on System Science and Engineering (ICSSE) Pub Date : 2012-08-02 DOI: 10.1109/ICSSE.2012.6257216
Jie Zhu, Yong Qin, Z. Zhao, Zi-yang Wang
{"title":"Research on evaluation of transfer efficiency of Rail transportation hub","authors":"Jie Zhu, Yong Qin, Z. Zhao, Zi-yang Wang","doi":"10.1109/ICSSE.2012.6257216","DOIUrl":"https://doi.org/10.1109/ICSSE.2012.6257216","url":null,"abstract":"Given the complex structure and diverse index in the evaluation of the transfer efficiency of Rail transport hub, this paper improves a traditional gray relation projection analysis method. Through calculating the different environmental distinguish coefficient and the weight based on the information entropy theory, it fully embodies the indirect effects on linkages between sub-factors in system, and improves the objectivity and reliability of the evaluation results.","PeriodicalId":113116,"journal":{"name":"2012 International Conference on System Science and Engineering (ICSSE)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131896245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Robust back propagation learning algorithm based on near sets 基于近集的鲁棒反向传播学习算法
2012 International Conference on System Science and Engineering (ICSSE) Pub Date : 2012-08-02 DOI: 10.1109/ICSSE.2012.6257141
Chih-Ching Hsiao, Chen-Chia Chuang, Jin-Tsong Jeng
{"title":"Robust back propagation learning algorithm based on near sets","authors":"Chih-Ching Hsiao, Chen-Chia Chuang, Jin-Tsong Jeng","doi":"10.1109/ICSSE.2012.6257141","DOIUrl":"https://doi.org/10.1109/ICSSE.2012.6257141","url":null,"abstract":"The traditional robust learning algorithms are based on the estimated errors, which is not correct in the early stage of the training process. Therefore, the use of those approaches still cannot provide very decent learning performance in face of outliers unless a set of good initial weights is used. In this paper, a novel approach, termed as NRBP (Near set based Robust Back Propagation learning algorithm) is proposed. In this learning algorithm, the training (estimated) data sets are separated into overlapping (or nonoverlapping) subsets of those data. It uses the set error measure instead of one-step error in robust back propagation based on near set. The set error measure is an estimated error measure between a subset of training data set and corresponding subset of estimated data set. Its benefit is it includes error messages and also reduces the outlier effect.","PeriodicalId":113116,"journal":{"name":"2012 International Conference on System Science and Engineering (ICSSE)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131313716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
The study of q-logarithmic modulation spectral normalization for robust speech recognition 基于q-对数调制谱归一化的鲁棒语音识别研究
2012 International Conference on System Science and Engineering (ICSSE) Pub Date : 2012-08-02 DOI: 10.1109/ICSSE.2012.6257173
Hao-Teng Fan, Che-hsien Hsu, J. Hung
{"title":"The study of q-logarithmic modulation spectral normalization for robust speech recognition","authors":"Hao-Teng Fan, Che-hsien Hsu, J. Hung","doi":"10.1109/ICSSE.2012.6257173","DOIUrl":"https://doi.org/10.1109/ICSSE.2012.6257173","url":null,"abstract":"This paper presents a novel use of the generalized logarithm operation (q-logarithm) in refining the modulation spectrum of speech features for noise-robust speech recognition. The resulting new method, generalized logarithmic modulation spectral mean normalization (GLMSMN), equalizes the average of the magnitude modulation spectrum in q-logarithmic domain for different utterances in order to alleviate the effect of noise. In the Aurora-2 connected-digit database and evaluation task, the presented GLMSMN operating on the MVN features reveals significant improvement in recognition accuracy in comparison with the MFCC baseline and MVN. The overall averaged recognition accuracy brought by GLMSMN can be nearly 90%.","PeriodicalId":113116,"journal":{"name":"2012 International Conference on System Science and Engineering (ICSSE)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121723507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
Intelligent Video Car Recorder systems 智能视频汽车记录系统
2012 International Conference on System Science and Engineering (ICSSE) Pub Date : 2012-08-02 DOI: 10.1109/ICSSE.2012.6257139
Dong-Han Lin, Chen-Chia Chuang, Jin-Tsong Jeng, C. Tao
{"title":"Intelligent Video Car Recorder systems","authors":"Dong-Han Lin, Chen-Chia Chuang, Jin-Tsong Jeng, C. Tao","doi":"10.1109/ICSSE.2012.6257139","DOIUrl":"https://doi.org/10.1109/ICSSE.2012.6257139","url":null,"abstract":"Video Car Recorder embedded into intelligent mobile devices is considered in this study. That is, the Lead Management System (LMS) is developed. The features of the LMS include recording instant car traveling screen, displaying the current location map, and capturing the current location data; namely, comprises latitude, longitude, speed, altitude and directional acceleration. Besides, the prominent feature of the entire application is that the system can be embedded into intelligent mobile devices for a variety of the iOS System. Because the iOS mobile devices with GPS and camera which is widely used, the Video Car Recorder application is not limited to the problems of hardware-integration. At the same time, the iOS SDK, Google Map API, Objective-C, and Xcode platform are applied to develop the application of intelligent mobile devices with Video Car Recorder. Consequently, the proposed application is a widely used and saving costs system.","PeriodicalId":113116,"journal":{"name":"2012 International Conference on System Science and Engineering (ICSSE)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116785426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Robust indirect adaptive fuzzy control based on the GFHM 基于GFHM的鲁棒间接自适应模糊控制
2012 International Conference on System Science and Engineering (ICSSE) Pub Date : 2012-08-02 DOI: 10.1109/ICSSE.2012.6257185
Z. Mingjun, Shao Cheng, Li Shikuan
{"title":"Robust indirect adaptive fuzzy control based on the GFHM","authors":"Z. Mingjun, Shao Cheng, Li Shikuan","doi":"10.1109/ICSSE.2012.6257185","DOIUrl":"https://doi.org/10.1109/ICSSE.2012.6257185","url":null,"abstract":"In this paper, a robust indirect adaptive fuzzy control algorithm based on the generalized fuzzy hyperbolic model (GFHM) for nonlinear system with uncertainties is proposed. The proposed control consists of two control terms. One is the certainty equivalent control and the other is the compensated control, which is obtained by bounded estimation in the online approximation of the uncertainty. The main advantage of the proposed control law is that the human knowledge about the plant under control is be used to design the controller and only one parameter vector in the adaptive mechanism is on-line adjusted. A simulation example is showed that the proposed controller provides good tracking performance.","PeriodicalId":113116,"journal":{"name":"2012 International Conference on System Science and Engineering (ICSSE)","volume":"9 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120977648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 7
The flood monitoring information system framework based on multi-source satellite remote sensing data 基于多源卫星遥感数据的洪水监测信息系统框架
2012 International Conference on System Science and Engineering (ICSSE) Pub Date : 2012-08-02 DOI: 10.1109/ICSSE.2012.6257196
Wei Zheng
{"title":"The flood monitoring information system framework based on multi-source satellite remote sensing data","authors":"Wei Zheng","doi":"10.1109/ICSSE.2012.6257196","DOIUrl":"https://doi.org/10.1109/ICSSE.2012.6257196","url":null,"abstract":"In this paper, the methodology of monitoring flood using multi-source satellite sensors was put forward in order to systematically utilize advantages of each data to utmostly acquire surface flood information. Huaihe River Basin flood in the summer 2007 in China was chosen as the study case. For large-scale flood monitoring and warning, the WSF(water surface fraction) method based on passive microwave remote sensing data ASMR-E was employed to reveal soil wetness and flood patterns of the whole Huaihe River Basin; For moderate-scale food monitoring of Huaihe River mainstream, the middle spatial resolution data MODIS was used to map maximum flood extent and flood duration; For detailed flood monitoring of hardest-hit area, the Radar data RADARSAT and optical data TM with higher spatial resolution were made use of fusion analysis to estimate the losses. The results showed that comprehensive and effective use of multi-source data could give reliable early flood warning, real-time monitoring of flood development, and rapid and accurate assessment of flood losses. The information system framework of monitoring flood using multi-source satellite sensors was feasible.","PeriodicalId":113116,"journal":{"name":"2012 International Conference on System Science and Engineering (ICSSE)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121057324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 14
Multiple models fusion for pattern classification on noise data 基于多模型融合的噪声数据模式分类
2012 International Conference on System Science and Engineering (ICSSE) Pub Date : 2012-08-02 DOI: 10.1109/ICSSE.2012.6257150
Bi Fan, Geng Zhang, Han-Xiong Li
{"title":"Multiple models fusion for pattern classification on noise data","authors":"Bi Fan, Geng Zhang, Han-Xiong Li","doi":"10.1109/ICSSE.2012.6257150","DOIUrl":"https://doi.org/10.1109/ICSSE.2012.6257150","url":null,"abstract":"An important characteristic of real-world learning process is that the data frequently contains uncertainties. The uncertainties in the datasets deteriorate the learning process. Hence, to properly represent and handle the uncertainty problem is one of the key issues in the decision learning system. This paper offers a multiple models fusion method to address the uncertainty problem, by conducting the fusion of two models, Bayesian classifier and Probabilistic based Noise Aware Support Vector Machine. Specifically, we take the advantage of noise-insensitive characteristic of the Naïve Bayesian classifier, to enhance the noise-tolerant ability of probabilistic information based Support Vector Machine. The method fuses the probabilistic decision information obtained from the two classifiers in a flexible way to give the final decision. Furthermore, the multiple models fusion method is evaluated on an artificial dataset for a classification task. The experiment results show good performance when compared with using only one learning technique in the noise environment.","PeriodicalId":113116,"journal":{"name":"2012 International Conference on System Science and Engineering (ICSSE)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126121208","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
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