Pub Date : 2009-06-17DOI: 10.1109/CCDC.2009.5192339
Lianxiong Gao, Jianping Wu, Rui Liu
Transport networks display the features of complex networks, in which the vertices importance measurement is crucial. After analyzing some classic importance measurements and the characteristics of transport networks, NodeRank, a new method based on PageRank algorithm, is proposed in this paper to measure the importance of vertices in transportation network. Then the constraint equation is deduced and the existence and uniqueness of solutions are presented. The solving algorithm is described and its convergence is analyzed. Finally, we present a case applying our method to mining key nodes in a real-world transport network.
{"title":"Key nodes mining in transport networks based in PageRank algorithm","authors":"Lianxiong Gao, Jianping Wu, Rui Liu","doi":"10.1109/CCDC.2009.5192339","DOIUrl":"https://doi.org/10.1109/CCDC.2009.5192339","url":null,"abstract":"Transport networks display the features of complex networks, in which the vertices importance measurement is crucial. After analyzing some classic importance measurements and the characteristics of transport networks, NodeRank, a new method based on PageRank algorithm, is proposed in this paper to measure the importance of vertices in transportation network. Then the constraint equation is deduced and the existence and uniqueness of solutions are presented. The solving algorithm is described and its convergence is analyzed. Finally, we present a case applying our method to mining key nodes in a real-world transport network.","PeriodicalId":127110,"journal":{"name":"2009 Chinese Control and Decision Conference","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131928479","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}
Pub Date : 2009-06-17DOI: 10.1109/CCDC.2009.5195160
Liandong Lin, Wei Qu, Xiang Yu
Clustering analysis is an important issue in data mining fields. Clustering in high dimensional space is especially difficult for a series of problems, such as the sparseness of spatial distribution of data, too much noise data points. Based on the analysis of current clustering algorithms can not get satisfying clustering results of high dimensional data. The theory of rough set and the idea of semi-supervised are introduced. And a semi-supervised grid clustering algorithm RSGrid based on the reduction of rough set theory is proposed. The theoretical analysis and experimental results indicate the algorithm can solve the problem of clustering in high dimensional space efficiently.
{"title":"A semi-supervised clustering algorithm based on rough reduction","authors":"Liandong Lin, Wei Qu, Xiang Yu","doi":"10.1109/CCDC.2009.5195160","DOIUrl":"https://doi.org/10.1109/CCDC.2009.5195160","url":null,"abstract":"Clustering analysis is an important issue in data mining fields. Clustering in high dimensional space is especially difficult for a series of problems, such as the sparseness of spatial distribution of data, too much noise data points. Based on the analysis of current clustering algorithms can not get satisfying clustering results of high dimensional data. The theory of rough set and the idea of semi-supervised are introduced. And a semi-supervised grid clustering algorithm RSGrid based on the reduction of rough set theory is proposed. The theoretical analysis and experimental results indicate the algorithm can solve the problem of clustering in high dimensional space efficiently.","PeriodicalId":127110,"journal":{"name":"2009 Chinese Control and Decision Conference","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131969515","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}
Pub Date : 2009-06-17DOI: 10.1109/CCDC.2009.5195055
Ying-wei Zhang, Hongqiang Li
In this paper, a novel fault monitoring and diagnosis approach based on kernel partial least squares(KPLS) is introduced. Unlike other nonlinear least squares (PLS) techniques, KPLS does not consider any nonlinear systems optimization procedures and has the characteristics similar to that of linear PLS. In this paper, KPLS provides good monitoring performance by finding those latent variables that present a nonlinear correlation with the response variables and at the same time improve model understanding. Simulation results show the proposed method can effectively capture the nonlinear relationship among variables and improve diagnosis performance.
{"title":"The fault monitoring and diagnosi based on KPLS","authors":"Ying-wei Zhang, Hongqiang Li","doi":"10.1109/CCDC.2009.5195055","DOIUrl":"https://doi.org/10.1109/CCDC.2009.5195055","url":null,"abstract":"In this paper, a novel fault monitoring and diagnosis approach based on kernel partial least squares(KPLS) is introduced. Unlike other nonlinear least squares (PLS) techniques, KPLS does not consider any nonlinear systems optimization procedures and has the characteristics similar to that of linear PLS. In this paper, KPLS provides good monitoring performance by finding those latent variables that present a nonlinear correlation with the response variables and at the same time improve model understanding. Simulation results show the proposed method can effectively capture the nonlinear relationship among variables and improve diagnosis performance.","PeriodicalId":127110,"journal":{"name":"2009 Chinese Control and Decision Conference","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129969866","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}
Pub Date : 2009-06-17DOI: 10.1109/CCDC.2009.5195305
WenJie Tian, Lan Ai, Yu Geng, Jicheng Liu
This paper provides an overview on immune clone selection algorithm for the automated design and optimization of fuzzy logic controller. A new optimization method for fuzzy logic controller design is proposed. The membership functions of input and output variables are defined by six parameters, which are adjusted to maximize the performance index of the controller by using immune clone selection algorithm. This method can shorten coding length, incarnate the characteristic of mutation and improve the capability of search and convergence of algorithm. Simulation experiment on water level controller is discussed by using above method. The simulation results show that the fuzzy logic controller based on immune clone selection algorithm avoids premature effectively and prove its feasibility.
{"title":"Immune clone selection algorithm for fuzzy logic controller design","authors":"WenJie Tian, Lan Ai, Yu Geng, Jicheng Liu","doi":"10.1109/CCDC.2009.5195305","DOIUrl":"https://doi.org/10.1109/CCDC.2009.5195305","url":null,"abstract":"This paper provides an overview on immune clone selection algorithm for the automated design and optimization of fuzzy logic controller. A new optimization method for fuzzy logic controller design is proposed. The membership functions of input and output variables are defined by six parameters, which are adjusted to maximize the performance index of the controller by using immune clone selection algorithm. This method can shorten coding length, incarnate the characteristic of mutation and improve the capability of search and convergence of algorithm. Simulation experiment on water level controller is discussed by using above method. The simulation results show that the fuzzy logic controller based on immune clone selection algorithm avoids premature effectively and prove its feasibility.","PeriodicalId":127110,"journal":{"name":"2009 Chinese Control and Decision Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130090762","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}
Pub Date : 2009-06-17DOI: 10.1109/CCDC.2009.5191821
J. Gong, Qian Li, Jiafu Tang
The cell assembly system is a new innovation of production strategies in the industry. There are many system performances needed to evaluate for the line-cell conversion, parts storage is one of them. In this paper, an overview of line-cell conversion to generate insights of the innovation is presented at first, and then a mathematical model is proposed to describe the performance of parts storage in a cell assembly system. At last, some numerical simulation experiments are designed and executed to evaluate the system performance of parts storage.
{"title":"Improving performance of parts storage through line-cell conversion","authors":"J. Gong, Qian Li, Jiafu Tang","doi":"10.1109/CCDC.2009.5191821","DOIUrl":"https://doi.org/10.1109/CCDC.2009.5191821","url":null,"abstract":"The cell assembly system is a new innovation of production strategies in the industry. There are many system performances needed to evaluate for the line-cell conversion, parts storage is one of them. In this paper, an overview of line-cell conversion to generate insights of the innovation is presented at first, and then a mathematical model is proposed to describe the performance of parts storage in a cell assembly system. At last, some numerical simulation experiments are designed and executed to evaluate the system performance of parts storage.","PeriodicalId":127110,"journal":{"name":"2009 Chinese Control and Decision Conference","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134068323","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}
Pub Date : 2009-06-17DOI: 10.1109/CCDC.2009.5192562
Wang De-ji, Xu Bo, Li Guangcai, Chen Guoqun
Optimal Model of Agricultural Structures is important in solving the “san nong” problem. In this paper, we introduce the yield function and price function of the product, which are regressed from the samples by SVM, into the genetic algorithm as the fitness function. This is a novel method for solving the Optimal Model of the Agricultural Structures. At last we put the method into Optimal Model Agricultural Structures for Hefei city and get the ideal result.
{"title":"Optimal Model of Agricultural Structure","authors":"Wang De-ji, Xu Bo, Li Guangcai, Chen Guoqun","doi":"10.1109/CCDC.2009.5192562","DOIUrl":"https://doi.org/10.1109/CCDC.2009.5192562","url":null,"abstract":"Optimal Model of Agricultural Structures is important in solving the “san nong” problem. In this paper, we introduce the yield function and price function of the product, which are regressed from the samples by SVM, into the genetic algorithm as the fitness function. This is a novel method for solving the Optimal Model of the Agricultural Structures. At last we put the method into Optimal Model Agricultural Structures for Hefei city and get the ideal result.","PeriodicalId":127110,"journal":{"name":"2009 Chinese Control and Decision Conference","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133934108","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}
Pub Date : 2009-06-17DOI: 10.1109/CCDC.2009.5195038
Pang Peilin, Ding Guangbin
The turbine-generator plays a crucial rule in modern industrial plant. The risk of turbine-generator set failure can be remarkably reduced if normal service condition can be arranged in advance. An effective approach based on wavelet neural network is presented for vibration signal analysis and fault diagnosis. The wavelet transform exhibits not only more comprehensive results, but also delivers a variety of possible explanations to the investigated problem. The main advantage of wavelet transform for signal analysis is that the wavelet coefficients are obtained by correlating vibration signal with the wavelet basis functions so that all possible fault patterns can be displayed by time-scale results. The feature vector obtained from wavelet transform coefficients are presented as input vector for neural network. The improved training algorithm is used to fulfill network training process and parameter initialization. From the output values of the neural network, the fault pattern is identified in accordance with the predefined fault feature vectors, which are obtained from practical experience. At the meantime, the convergence property of wavelet network for fault diagnosis is discussed. The experiment results demonstrate that the proposed method is effective and accurate.
{"title":"Vibration diagnosis method based on wavelet analysis and neural network for turbine-generator","authors":"Pang Peilin, Ding Guangbin","doi":"10.1109/CCDC.2009.5195038","DOIUrl":"https://doi.org/10.1109/CCDC.2009.5195038","url":null,"abstract":"The turbine-generator plays a crucial rule in modern industrial plant. The risk of turbine-generator set failure can be remarkably reduced if normal service condition can be arranged in advance. An effective approach based on wavelet neural network is presented for vibration signal analysis and fault diagnosis. The wavelet transform exhibits not only more comprehensive results, but also delivers a variety of possible explanations to the investigated problem. The main advantage of wavelet transform for signal analysis is that the wavelet coefficients are obtained by correlating vibration signal with the wavelet basis functions so that all possible fault patterns can be displayed by time-scale results. The feature vector obtained from wavelet transform coefficients are presented as input vector for neural network. The improved training algorithm is used to fulfill network training process and parameter initialization. From the output values of the neural network, the fault pattern is identified in accordance with the predefined fault feature vectors, which are obtained from practical experience. At the meantime, the convergence property of wavelet network for fault diagnosis is discussed. The experiment results demonstrate that the proposed method is effective and accurate.","PeriodicalId":127110,"journal":{"name":"2009 Chinese Control and Decision Conference","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134336442","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}
Pub Date : 2009-06-17DOI: 10.1109/CCDC.2009.5195189
Yu-Long Wang, Ai-Chun Qi, Tian-Bao Wang, Heng Wang
This paper studies the problem of designing robust H∞ controllers for networked control systems (NCSs) with both network-induced time delay and packet dropout by using active varying sampling period method, where the sampling period switches in a finite set. An active varying sampling period method using both clock-driven and event-driven sensor is proposed, then by modeling the system with varying sampling period as a switched system, H∞ controllers are designed by using LMI-based method. The simulation results illustrate the effectiveness of the active varying sampling period method and the proposed H∞ controller design.
{"title":"Active varying sampling period-based networked systems H∞ control","authors":"Yu-Long Wang, Ai-Chun Qi, Tian-Bao Wang, Heng Wang","doi":"10.1109/CCDC.2009.5195189","DOIUrl":"https://doi.org/10.1109/CCDC.2009.5195189","url":null,"abstract":"This paper studies the problem of designing robust H∞ controllers for networked control systems (NCSs) with both network-induced time delay and packet dropout by using active varying sampling period method, where the sampling period switches in a finite set. An active varying sampling period method using both clock-driven and event-driven sensor is proposed, then by modeling the system with varying sampling period as a switched system, H∞ controllers are designed by using LMI-based method. The simulation results illustrate the effectiveness of the active varying sampling period method and the proposed H∞ controller design.","PeriodicalId":127110,"journal":{"name":"2009 Chinese Control and Decision Conference","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131707359","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}
Pub Date : 2009-06-17DOI: 10.1109/CCDC.2009.5191631
Bi Hong-bo, Gao Bing-kun, Zhang Yu-bo
The oil-field power system and provincial power system belong to the different power system, which purchases the maximal economic benefit respectively. Therefore, under the security restraint, how to cooperate each source output to meet the need of economic operation of the oil-field power system adaptively becomes a very important problem. The mathematical model of oil-field power system output optimization is set up under the market condition, which takes the minimal power cost as the objective function, whose constraints include power supply balance, power station output, line security. At the same time, considering the influence on the actual power price of the net losses generated by the difference of the geographical different sources the modified power price is introduced. Furthermore, the improved genetic algorithm using the chaotic searching method is proposed and applied to the optimization for the oil-field power system. Results show that the improved algorithm can reduce the power costs of the oil-field power system.
{"title":"Research on optimization for the open multi-sources oil-field power net output","authors":"Bi Hong-bo, Gao Bing-kun, Zhang Yu-bo","doi":"10.1109/CCDC.2009.5191631","DOIUrl":"https://doi.org/10.1109/CCDC.2009.5191631","url":null,"abstract":"The oil-field power system and provincial power system belong to the different power system, which purchases the maximal economic benefit respectively. Therefore, under the security restraint, how to cooperate each source output to meet the need of economic operation of the oil-field power system adaptively becomes a very important problem. The mathematical model of oil-field power system output optimization is set up under the market condition, which takes the minimal power cost as the objective function, whose constraints include power supply balance, power station output, line security. At the same time, considering the influence on the actual power price of the net losses generated by the difference of the geographical different sources the modified power price is introduced. Furthermore, the improved genetic algorithm using the chaotic searching method is proposed and applied to the optimization for the oil-field power system. Results show that the improved algorithm can reduce the power costs of the oil-field power system.","PeriodicalId":127110,"journal":{"name":"2009 Chinese Control and Decision Conference","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131732350","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}
Pub Date : 2009-06-17DOI: 10.1109/CCDC.2009.5192110
Yanling Hao, Zhiping Liu
Aim at the precision limitation for calculating angular velocity because of installation errors of accelerometer in the gyro free strapdown inertial navigation system (GFSINS), a calibration method of installation error parameters is put forward. Based on a six-accelerometer configuration scheme, the calculating method of angular velocity and linear acceleration is analyzed, and the accelerometer output error resulting from accelerometer installation errors is deduced. On the stationary base, the accelerometer output value is obtained in the three different positions by twice axis rotation of inertial measurement unit, then, all the installation error parameters of accelerometer are given. Simulation results show that the calibrating method is feasible. After calibration and compensation for installation errors, the calculation precision of angular velocity is improved by 1 order of magnitude in 100s time.
{"title":"Analysis and calibration on installation errors of accelerometer in GFSINS","authors":"Yanling Hao, Zhiping Liu","doi":"10.1109/CCDC.2009.5192110","DOIUrl":"https://doi.org/10.1109/CCDC.2009.5192110","url":null,"abstract":"Aim at the precision limitation for calculating angular velocity because of installation errors of accelerometer in the gyro free strapdown inertial navigation system (GFSINS), a calibration method of installation error parameters is put forward. Based on a six-accelerometer configuration scheme, the calculating method of angular velocity and linear acceleration is analyzed, and the accelerometer output error resulting from accelerometer installation errors is deduced. On the stationary base, the accelerometer output value is obtained in the three different positions by twice axis rotation of inertial measurement unit, then, all the installation error parameters of accelerometer are given. Simulation results show that the calibrating method is feasible. After calibration and compensation for installation errors, the calculation precision of angular velocity is improved by 1 order of magnitude in 100s time.","PeriodicalId":127110,"journal":{"name":"2009 Chinese Control and Decision Conference","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131781237","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}
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