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2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI)最新文献

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Assessment on the water security of Zhangye based on the DPSIR model 基于DPSIR模型的张掖水安全评价
2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI) Pub Date : 2012-10-01 DOI: 10.1109/ICACI.2012.6463289
Liping Liu, Deshan Tang, Tian-Shen Chen
{"title":"Assessment on the water security of Zhangye based on the DPSIR model","authors":"Liping Liu, Deshan Tang, Tian-Shen Chen","doi":"10.1109/ICACI.2012.6463289","DOIUrl":"https://doi.org/10.1109/ICACI.2012.6463289","url":null,"abstract":"Water resources are the most important strategic resource in Northwest. Poor water condition is an important reason for fragile ecological environment, economic backwardness, and concentrated poverty population. Deep study of water security is an effective way to promote the protection of the western development strategy. This paper reviews the forefront progress of both international and domestic, conceptualizes water security, constructs DPSIR model, and emphasizes the seriousness of the water security issues caused by the high intensity of human activity, then explores the driving, pressure, influence, status and respond factors of water security. Zhangye region is taken as a case study area, and the AHP and entropy weight method is employed to determine the weight factors. Finally, the gray theory method is used to evaluate water security in 2004-2010 in Zhangye. The conclusions are that: the water security of Zhangye City has increased steadily and it has taken a greater progress since 2004 to 2010. Adverse natural factors are still the main reason for water security issues. In addition, the facts of high intensity of human activities, less developed economic status and the negative system of management further conduce social resources scarcity, which aggravate the water safety problems.","PeriodicalId":404759,"journal":{"name":"2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122248064","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
Computationally efficient TOA estimation for UWB signal 超宽带信号的高效TOA估计
2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI) Pub Date : 2012-10-01 DOI: 10.1109/ICACI.2012.6463351
Fangqiu Wang, Xiaofei Zhang, Chen Chen
{"title":"Computationally efficient TOA estimation for UWB signal","authors":"Fangqiu Wang, Xiaofei Zhang, Chen Chen","doi":"10.1109/ICACI.2012.6463351","DOIUrl":"https://doi.org/10.1109/ICACI.2012.6463351","url":null,"abstract":"Precision ultra-wideband (UWB) ranging and positioning require accurate estimation of time of arrival (TOA). In this paper, we proposed a computationally efficient algorithm to estimate the TOA for UWB signal. In the algorithm we first obtain the propagator operator by using the Propagator Method (PM), and then we adopt the ESPRIT Method estimating the TOA directly. This algorithm requires no peak searching compared to PM, and reduces the number of eigen-decomposition calculation times compared to ESPRIT, which is low complexity and computationally efficient, and the performance is close to ESPRIT. The simulation results validate the proposed algorithm.","PeriodicalId":404759,"journal":{"name":"2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122300356","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
Delay-dependent passivity and passification of stochastic impulsive neutral systems with mixed delays 混合时滞随机脉冲中立型系统的时滞相关无源性和钝化
2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI) Pub Date : 2012-10-01 DOI: 10.1109/ICACI.2012.6463182
Xiaoning Duan
{"title":"Delay-dependent passivity and passification of stochastic impulsive neutral systems with mixed delays","authors":"Xiaoning Duan","doi":"10.1109/ICACI.2012.6463182","DOIUrl":"https://doi.org/10.1109/ICACI.2012.6463182","url":null,"abstract":"This paper is concerned with the problem of delay-dependent passivity analysis and passification for a class of stochastic impulsive neutral systems with mixed delays. To reflect more realistic dynamical behaviors of the system, the stochastic disturbances are considered, which are given in the form of a Brownian motion. By constructing a proper stochastic Lyapunov-Krasovskii function as well as the linear matrix inequalities (LMIs) technique, some novel sufficient conditions are derived to ensure the delay-dependent passivity/passification performance in terms of LMIs. Finally, a numerical example is given to illustrate the theoretical results.","PeriodicalId":404759,"journal":{"name":"2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126772111","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
The research of intelligent vehicle's steering control system based on fuzzy control 基于模糊控制的智能汽车转向控制系统的研究
2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI) Pub Date : 2012-10-01 DOI: 10.1109/ICACI.2012.6463209
Qingqian Liu, Bo Wang, Xiaowei Ma
{"title":"The research of intelligent vehicle's steering control system based on fuzzy control","authors":"Qingqian Liu, Bo Wang, Xiaowei Ma","doi":"10.1109/ICACI.2012.6463209","DOIUrl":"https://doi.org/10.1109/ICACI.2012.6463209","url":null,"abstract":"The intelligent vehicle steering control is an important part of Intelligent Vehicle System. This article explores the kinematical model of vehicle and the driver's behavior for the issue of the vehicle steering, and it proposes an expertise-based fuzzy control method that is built on a foundation of the visual image processing technology. This article also deeply analyzes the parameters of the control method and then creates a fuzzy controller of vehicle steering control. The simulation reveals that the controller's control effect is good, and it can imitate the driver's intelligent behavior well.","PeriodicalId":404759,"journal":{"name":"2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120949949","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
A path planning algorithm with a capsule-like restricted searching area based on vehicle navigation system 一种基于车辆导航系统的类胶囊受限搜索区域路径规划算法
2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI) Pub Date : 2012-10-01 DOI: 10.1109/ICACI.2012.6463206
Xiaowei Ma, Lingjuan Miao, Qingqian Liu
{"title":"A path planning algorithm with a capsule-like restricted searching area based on vehicle navigation system","authors":"Xiaowei Ma, Lingjuan Miao, Qingqian Liu","doi":"10.1109/ICACI.2012.6463206","DOIUrl":"https://doi.org/10.1109/ICACI.2012.6463206","url":null,"abstract":"In order to further improve the efficiency and reliability of current path planning algorithms applied to embedded vehicle navigation systems, a novel path planning algorithm is proposed in this paper based on a concise topology electronic map. In the proposed algorithm, the traditional searching area is optimized by tackling the path planning problem in a capsule-like restricted area. Furthermore, the feasibility and reliability of the algorithm is guaranteed by setting the dynamic parameter. Simulation results verify that the proposed algorithm finds the optimal shortest path in a short time and performs better than conventional algorithms in terms of effectiveness and reliability.","PeriodicalId":404759,"journal":{"name":"2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI)","volume":"184 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116631339","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
Using k-harmonic means clustering for the initialization of the clustering method based on one-class support vector machines 采用k-调和均值聚类进行初始化，提出了基于一类支持向量机的聚类方法
2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI) Pub Date : 2012-10-01 DOI: 10.1109/ICACI.2012.6463173
Lei Gu
{"title":"Using k-harmonic means clustering for the initialization of the clustering method based on one-class support vector machines","authors":"Lei Gu","doi":"10.1109/ICACI.2012.6463173","DOIUrl":"https://doi.org/10.1109/ICACI.2012.6463173","url":null,"abstract":"The initialization of one clustering method based on one-class support vector machines often employs random samples. This way can lead to the unstable clustering results. In this paper, the k-harmonic means clustering takes the place of this random initialization. To investigate the effectiveness of the novel proposed approach, several experiments are done on one artificial dataset and two real datasets. Experimental results show that our presented method can not only obtain the stable clustering accuracies, but aloes improve the clustering performance significantly compared to other different initialization, such as random initialization and k-means initialization.","PeriodicalId":404759,"journal":{"name":"2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125266288","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
Face recognition algorithm combined with DCT, PCA and BPNN 结合DCT、PCA和bp神经网络的人脸识别算法
2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI) Pub Date : 2012-10-01 DOI: 10.1109/ICACI.2012.6463254
Guoliang Yang, Linjia Xu
{"title":"Face recognition algorithm combined with DCT, PCA and BPNN","authors":"Guoliang Yang, Linjia Xu","doi":"10.1109/ICACI.2012.6463254","DOIUrl":"https://doi.org/10.1109/ICACI.2012.6463254","url":null,"abstract":"This paper provides an integrated algorithm to deal with face recognition. It uses discrete cosine transform and principal component analysis to reduce dimensions and extract face features, and then trains and tests face images through the BP neural network classifier. It also seeks for other method such as the nearest neighbor classifier to have a comparison with BP neural network. Simulation result shows the effectiveness of this algorithm.","PeriodicalId":404759,"journal":{"name":"2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131372137","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
A new association rules mining method based on ontology theory 一种基于本体理论的关联规则挖掘新方法
2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI) Pub Date : 2012-10-01 DOI: 10.1109/ICACI.2012.6463170
Yongqing Wang, Yan Chen
{"title":"A new association rules mining method based on ontology theory","authors":"Yongqing Wang, Yan Chen","doi":"10.1109/ICACI.2012.6463170","DOIUrl":"https://doi.org/10.1109/ICACI.2012.6463170","url":null,"abstract":"Association rules mining is a process of finding patterns from a very large volumes of data. The Apriori algorithm is the best-known association rules mining algorithm, whose objective is to find all co-occurrence relationships between data items. In this paper, a methodology that combines the Apriori algorithm with a domain-specific ontology is proposed. This method is to effectively utilize domain ontologies to find multiple layer association rules.","PeriodicalId":404759,"journal":{"name":"2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133134901","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
A research on determinants of floating women's income with Bayesian Networks 基于贝叶斯网络的流动女性收入决定因素研究
2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI) Pub Date : 2012-10-01 DOI: 10.1109/ICACI.2012.6463328
Yingyu Ge, Chunping Li
{"title":"A research on determinants of floating women's income with Bayesian Networks","authors":"Yingyu Ge, Chunping Li","doi":"10.1109/ICACI.2012.6463328","DOIUrl":"https://doi.org/10.1109/ICACI.2012.6463328","url":null,"abstract":"Based on the survey of floating women in Jiangsu province, the article establishes a directed acyclic graph of factors influence income of floating women by using Bayesian Networks. The result indicates that not all the individual characteristics have a direct effect on income. The relationships between income and individual characteristics are complicated. Age has a direct impact on education level and marital status. Domicile has a direct impact on education level. Educational level and marital status influence floating women's job. And different jobs offer different salary. So age, domicile, education level, and marital status have indirect influence on income through the job of floating women.","PeriodicalId":404759,"journal":{"name":"2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI)","volume":"79 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116584682","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
A wavelet packet diagnosis system based on rough set theory 基于粗糙集理论的小波包诊断系统
2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI) Pub Date : 2012-10-01 DOI: 10.1109/ICACI.2012.6463164
Yingkai Sun, Hai Chen
{"title":"A wavelet packet diagnosis system based on rough set theory","authors":"Yingkai Sun, Hai Chen","doi":"10.1109/ICACI.2012.6463164","DOIUrl":"https://doi.org/10.1109/ICACI.2012.6463164","url":null,"abstract":"The wavelet packet analysis was adopted in acquisition of fault diagnosis system's characteristic parameter. The application of rough set theory in parameter's attribute optimization was explored. The unnecessary attributes were eliminated with reduction algorithm. The inner redundancy of fault diagnosis system's condition attributes is revealed. The complexity of neural network's structure is also decreased. The result of attribute reduction is given finally.","PeriodicalId":404759,"journal":{"name":"2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115137286","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
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