Pub Date : 2009-05-23DOI: 10.1109/IWISA.2009.5072611
Yuling Tian, Peng Ren
In biological immune system, B-cells secrete large numbers of antibodies to recognize and eliminate the antigens. Inspired by the relationship of B-cells and antibodies, an effective immune model is presented in this paper. As its learning capability, this model can recognize not only the existing antigens but also the antigens that are unknown. The structure of the model and the detailed algorithm are given in this paper. And the validity of the model is proved through an experiment of motor fault data clustering. Keywords-artificial immune system; clustering; B-cell; antibody I. INTRODUCTION Currently, information technology develops very fast. So, huge information is produced, and data mining can transform them into useful knowledge. Clustering is an important domain of data mining. It can find out the distributing rule of data character through comparing the comparability and diversity of data, and help researchers to obtain more profound comprehension and cognition (1). But the traditional clustering algorithm are deficient on clustering precision and convergent speed, such as k-means algorithm, Bayesian learning algorithm, fuzzy C means algorithm (FCM), etc.
{"title":"A Clustering Model Inspired by Humoral Immunity","authors":"Yuling Tian, Peng Ren","doi":"10.1109/IWISA.2009.5072611","DOIUrl":"https://doi.org/10.1109/IWISA.2009.5072611","url":null,"abstract":"In biological immune system, B-cells secrete large numbers of antibodies to recognize and eliminate the antigens. Inspired by the relationship of B-cells and antibodies, an effective immune model is presented in this paper. As its learning capability, this model can recognize not only the existing antigens but also the antigens that are unknown. The structure of the model and the detailed algorithm are given in this paper. And the validity of the model is proved through an experiment of motor fault data clustering. Keywords-artificial immune system; clustering; B-cell; antibody I. INTRODUCTION Currently, information technology develops very fast. So, huge information is produced, and data mining can transform them into useful knowledge. Clustering is an important domain of data mining. It can find out the distributing rule of data character through comparing the comparability and diversity of data, and help researchers to obtain more profound comprehension and cognition (1). But the traditional clustering algorithm are deficient on clustering precision and convergent speed, such as k-means algorithm, Bayesian learning algorithm, fuzzy C means algorithm (FCM), etc.","PeriodicalId":6327,"journal":{"name":"2009 International Workshop on Intelligent Systems and Applications","volume":"49 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2009-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79856052","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 : 2009-05-23DOI: 10.1109/IWISA.2009.5072886
Jun Li, Chengrong Xie
In this paper, we study the problem of generating chaotic attractors by using a switching type of piecewise linear controller. A new chaotic system is generated by designing a switching piecewise-linear controller . Some basic dynamical properties, such as Lyapunov exponents, fractal dimension, equilibrium and chaotic dynamical behaviors of the new chaotic system are studied. Furthermore, dynamical structures also have been discussed by parameters and controller variation, either numerically or analytically. Of particular interest is the fact that chaotic system can generate two opposite direction attractors in a wide parameter range. According to its geometric locations, two attractors are called upper-attractor and lower-attractor. The obtained results show clearly that the system discussed in this paper is a new chaotic system and deserves further detailed investigation.
{"title":"Generating New Chaos with a Switching Piecewise-Linear Controller","authors":"Jun Li, Chengrong Xie","doi":"10.1109/IWISA.2009.5072886","DOIUrl":"https://doi.org/10.1109/IWISA.2009.5072886","url":null,"abstract":"In this paper, we study the problem of generating chaotic attractors by using a switching type of piecewise linear controller. A new chaotic system is generated by designing a switching piecewise-linear controller . Some basic dynamical properties, such as Lyapunov exponents, fractal dimension, equilibrium and chaotic dynamical behaviors of the new chaotic system are studied. Furthermore, dynamical structures also have been discussed by parameters and controller variation, either numerically or analytically. Of particular interest is the fact that chaotic system can generate two opposite direction attractors in a wide parameter range. According to its geometric locations, two attractors are called upper-attractor and lower-attractor. The obtained results show clearly that the system discussed in this paper is a new chaotic system and deserves further detailed investigation.","PeriodicalId":6327,"journal":{"name":"2009 International Workshop on Intelligent Systems and Applications","volume":"91 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2009-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84649258","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 : 2009-05-23DOI: 10.1109/IWISA.2009.5072664
Yu Yue, Zhixin Chen
A novel algorithm for the naturally sampled SVPWM in overmodulation region is proposed in this paper, the comparison between naturally sampled SVPWM and conventional SVPWM in overmodulation region is carried out. It was proved that naturally sampled SVPWM could be used not only in under modulation but also in overmodulation region by the results of analysis and simulation. The work was done by this paper shows a promising use of the naturally sampled SVPWM. The obviously advantage is that it could be implemented by using DSP with only simplified computation and short time of on line calculation, or just by using analog circuits without the help of microprocessor at all. All the work did by this paper provide a platform for the implementation of naturally sampled SVPWM operating in under modulation and over modulation region.
{"title":"A Novel Naturally Sampled Space Vector Pulse Width Modulation Algorithm","authors":"Yu Yue, Zhixin Chen","doi":"10.1109/IWISA.2009.5072664","DOIUrl":"https://doi.org/10.1109/IWISA.2009.5072664","url":null,"abstract":"A novel algorithm for the naturally sampled SVPWM in overmodulation region is proposed in this paper, the comparison between naturally sampled SVPWM and conventional SVPWM in overmodulation region is carried out. It was proved that naturally sampled SVPWM could be used not only in under modulation but also in overmodulation region by the results of analysis and simulation. The work was done by this paper shows a promising use of the naturally sampled SVPWM. The obviously advantage is that it could be implemented by using DSP with only simplified computation and short time of on line calculation, or just by using analog circuits without the help of microprocessor at all. All the work did by this paper provide a platform for the implementation of naturally sampled SVPWM operating in under modulation and over modulation region.","PeriodicalId":6327,"journal":{"name":"2009 International Workshop on Intelligent Systems and Applications","volume":"17 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2009-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85468495","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 : 2009-05-23DOI: 10.1109/IWISA.2009.5072753
Huaigang Zang, Simeng Feng
Based on the design concept of virtual instrument and the design method of function modulation, using PC machine and data acquisition card as hardware system, proposed a design of sewage multi-parameter online monitoring system which based on application program platform of Lab VIEW. The system has friendly human-machine interface, the function is comprehensive and it is easy to operate. It has achieved the sewage multiparameter collecting, recording, controlling and management automatic, and enhanced the automaticity of the sewage collecting and examination. The test indicated that the system worked well, achieved the anticipated target.
{"title":"Application of Virtual Instrument in Sewage Multi-Parameter Online Monitoring System","authors":"Huaigang Zang, Simeng Feng","doi":"10.1109/IWISA.2009.5072753","DOIUrl":"https://doi.org/10.1109/IWISA.2009.5072753","url":null,"abstract":"Based on the design concept of virtual instrument and the design method of function modulation, using PC machine and data acquisition card as hardware system, proposed a design of sewage multi-parameter online monitoring system which based on application program platform of Lab VIEW. The system has friendly human-machine interface, the function is comprehensive and it is easy to operate. It has achieved the sewage multiparameter collecting, recording, controlling and management automatic, and enhanced the automaticity of the sewage collecting and examination. The test indicated that the system worked well, achieved the anticipated target.","PeriodicalId":6327,"journal":{"name":"2009 International Workshop on Intelligent Systems and Applications","volume":"T167 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2009-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82303359","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 : 2009-05-23DOI: 10.1109/IWISA.2009.5073165
Fang Zhou, Jianheng Ji, De-zhen Feng
Based on the fuzzy classifying approach, the paper puts forwards a diagnosis algorithm of Back-propagation Neural Network. For some complexity environments, the traditional Backpropagation Neural Network has some limitations on classification. The paper applies fuzzy model on Neural Network structure, by using classifying variance and energy function to adjust the convergence of the Neural Network. With the improved nonlinear mapping property, the diagnostic processing shows perfect results with identifying ratio of 100 percent, while the traditional method is 65 percent only. Keywords—Classification, Neural network, Diagnosis, Back propagation
{"title":"The Application of BP Neural Network on Mechanical Failure Classification","authors":"Fang Zhou, Jianheng Ji, De-zhen Feng","doi":"10.1109/IWISA.2009.5073165","DOIUrl":"https://doi.org/10.1109/IWISA.2009.5073165","url":null,"abstract":"Based on the fuzzy classifying approach, the paper puts forwards a diagnosis algorithm of Back-propagation Neural Network. For some complexity environments, the traditional Backpropagation Neural Network has some limitations on classification. The paper applies fuzzy model on Neural Network structure, by using classifying variance and energy function to adjust the convergence of the Neural Network. With the improved nonlinear mapping property, the diagnostic processing shows perfect results with identifying ratio of 100 percent, while the traditional method is 65 percent only. Keywords—Classification, Neural network, Diagnosis, Back propagation","PeriodicalId":6327,"journal":{"name":"2009 International Workshop on Intelligent Systems and Applications","volume":"92 1","pages":"1-3"},"PeriodicalIF":0.0,"publicationDate":"2009-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80412706","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 : 2009-05-23DOI: 10.1109/IWISA.2009.5072733
Hui Li, E. Yan, Yi Xiao, Yukun Wu, Xiaoyun Yang, Ying Fan
The two sided mutual anchoring thin retaining wall is a new type of structure, the action mechanism is very complicated. It has aroused the widespread concern of the engineering community how to properly select the main filling materials of high embankment. The effect law of the index of elastic modulus on the stress of tensive bar and the lateral earth pressure are obtained based on the finite element analysis ANSYS software combining an engineering sample. Variation of elastic modulus index of main filling materials will have bigger influence on lateral earth pressure and the stress of tensive bar. These results in this paper indicate that enhances elastic modulus of main filling material can improve mechanical properties and provides the basis for the main filling materials of high filling embankment structure.
{"title":"Analysis for Elastic Modulus of Main Fill Materials to Stress Properties of High Fill Embankment Structure","authors":"Hui Li, E. Yan, Yi Xiao, Yukun Wu, Xiaoyun Yang, Ying Fan","doi":"10.1109/IWISA.2009.5072733","DOIUrl":"https://doi.org/10.1109/IWISA.2009.5072733","url":null,"abstract":"The two sided mutual anchoring thin retaining wall is a new type of structure, the action mechanism is very complicated. It has aroused the widespread concern of the engineering community how to properly select the main filling materials of high embankment. The effect law of the index of elastic modulus on the stress of tensive bar and the lateral earth pressure are obtained based on the finite element analysis ANSYS software combining an engineering sample. Variation of elastic modulus index of main filling materials will have bigger influence on lateral earth pressure and the stress of tensive bar. These results in this paper indicate that enhances elastic modulus of main filling material can improve mechanical properties and provides the basis for the main filling materials of high filling embankment structure.","PeriodicalId":6327,"journal":{"name":"2009 International Workshop on Intelligent Systems and Applications","volume":"84 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2009-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80453437","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 : 2009-05-23DOI: 10.1109/IWISA.2009.5073118
Dong Nie, Kyu-Phil Han, Heng-Suk Lee
To solve the general problems of genetic algorithms applied in stereo matching, two measures are proposed. Firstly, the strategy of the simplified population-based incremental learning (PBIL) is adopted to decrease the problems in memory consumption and searching inefficiency, as well as a scheme controlling the distance of neighbors for disparity smoothness is inserted to obtain a wide-area consistency of disparities. In addition, an alternative version of the proposed algorithm without using a probability vector is also presented for simpler set-ups. Secondly, to decrease the running time further, a model of the proposed algorithm which can be run on programmable graphics-hardware (GPU) is newly given. The algorithms are implemented on the CPU as well as the GPU and evaluated by experiments. The experimental results show the proposed algorithm has better performance than traditional BMA methods with a deliberate relaxation and its modified version in both running speed and stability. The comparison in computation times for the algorithm both on GPU and CPU shows that the former has more speed-up than the latter, the bigger the image size is.
{"title":"Stereo Matching Algorithm Using Population-Based Incremental Learning on GPU","authors":"Dong Nie, Kyu-Phil Han, Heng-Suk Lee","doi":"10.1109/IWISA.2009.5073118","DOIUrl":"https://doi.org/10.1109/IWISA.2009.5073118","url":null,"abstract":"To solve the general problems of genetic algorithms applied in stereo matching, two measures are proposed. Firstly, the strategy of the simplified population-based incremental learning (PBIL) is adopted to decrease the problems in memory consumption and searching inefficiency, as well as a scheme controlling the distance of neighbors for disparity smoothness is inserted to obtain a wide-area consistency of disparities. In addition, an alternative version of the proposed algorithm without using a probability vector is also presented for simpler set-ups. Secondly, to decrease the running time further, a model of the proposed algorithm which can be run on programmable graphics-hardware (GPU) is newly given. The algorithms are implemented on the CPU as well as the GPU and evaluated by experiments. The experimental results show the proposed algorithm has better performance than traditional BMA methods with a deliberate relaxation and its modified version in both running speed and stability. The comparison in computation times for the algorithm both on GPU and CPU shows that the former has more speed-up than the latter, the bigger the image size is.","PeriodicalId":6327,"journal":{"name":"2009 International Workshop on Intelligent Systems and Applications","volume":"41 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2009-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81447499","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 : 2009-05-23DOI: 10.1109/IWISA.2009.5072742
Jianpo Li, Xiaojuan Chen, Chunming Wu
The fault diagnosis of power transformer is an important guarantee technique for safe and reliable running of power system. Combining the dissolved gases analysis and grey relational theory, a new comprehensive relational grade theory is given, which combines grey area relational grade and grey slope relational grade. The method is applied to expert system of transformer fault diagnosis and improves effectively the running and maintenance of power transformer. The paper introduces the concept of example reasoning. By calculating the relational grade between detected data and normative mode vector in source sample database, the fault style can be confirmed. The database and repository in this expert system is an open system. New fault sample can be added into the system, and repository can be classed and modified by experts.
{"title":"Application of Comprehensive Relational Grade Theory in Expert System of Transformer Fault Diagnosis","authors":"Jianpo Li, Xiaojuan Chen, Chunming Wu","doi":"10.1109/IWISA.2009.5072742","DOIUrl":"https://doi.org/10.1109/IWISA.2009.5072742","url":null,"abstract":"The fault diagnosis of power transformer is an important guarantee technique for safe and reliable running of power system. Combining the dissolved gases analysis and grey relational theory, a new comprehensive relational grade theory is given, which combines grey area relational grade and grey slope relational grade. The method is applied to expert system of transformer fault diagnosis and improves effectively the running and maintenance of power transformer. The paper introduces the concept of example reasoning. By calculating the relational grade between detected data and normative mode vector in source sample database, the fault style can be confirmed. The database and repository in this expert system is an open system. New fault sample can be added into the system, and repository can be classed and modified by experts.","PeriodicalId":6327,"journal":{"name":"2009 International Workshop on Intelligent Systems and Applications","volume":"46 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2009-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82494946","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 : 2009-05-23DOI: 10.1109/IWISA.2009.5072980
Ye Xu, Zhuo Wang, Wen-bo Zhang
Distributed fusion algorithm and its model(DFM) are discussed for oil forecast in this paper. DFM comprises a Global Fusion Center(GFC) and several Local Fusion Units(LFU) tightly connecting with each other. LFU performs fusion through two steps: the feature-level fusion that analyzes qualitative data through classifying analysis method and extracts quantitative data through BP Neural Network method; and the decision-level fusion that conducts decision-level analysis on the results of feature-level fusion through Bayesian Network. GFC makes the final decision on the LFU results. Experiments proves that DFM is efficient and acceptable since it decreases global complexity by separating one whole fusion tasks into several local fusion ones. Keywords-Information Fusion; Distributed fusion
{"title":"On a Distributed Fusion Algorithm in Oil Forecast","authors":"Ye Xu, Zhuo Wang, Wen-bo Zhang","doi":"10.1109/IWISA.2009.5072980","DOIUrl":"https://doi.org/10.1109/IWISA.2009.5072980","url":null,"abstract":"Distributed fusion algorithm and its model(DFM) are discussed for oil forecast in this paper. DFM comprises a Global Fusion Center(GFC) and several Local Fusion Units(LFU) tightly connecting with each other. LFU performs fusion through two steps: the feature-level fusion that analyzes qualitative data through classifying analysis method and extracts quantitative data through BP Neural Network method; and the decision-level fusion that conducts decision-level analysis on the results of feature-level fusion through Bayesian Network. GFC makes the final decision on the LFU results. Experiments proves that DFM is efficient and acceptable since it decreases global complexity by separating one whole fusion tasks into several local fusion ones. Keywords-Information Fusion; Distributed fusion","PeriodicalId":6327,"journal":{"name":"2009 International Workshop on Intelligent Systems and Applications","volume":"357 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2009-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82626341","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 : 2009-05-23DOI: 10.1109/IWISA.2009.5073082
Bo Wang, W. An, Yiyu Zhou
In allusion to sensor management problem of continual midcourse object tracking in the space tracking and surveillance system, a novel optimized objective function was proposed according to analysis of its restriction. Furthermore, on the basis of analyzing the disadvantages of binary particle swarm optimization based sensor management, a novel method based on real-number particle swarm optimization was proposed through dimensionality reduction and position vector improvement. Ultimately, simulation about classical midcourse object tracking scenario was executed, and the performance of several methods were compared in detail. The simulation results indicated that the novel optimized objective function could schedule sensors effectively; moreover, the proposed sensor management was a more efficient method.
{"title":"Research on Sensor Management Algorithm of Midcourse Object Tracking","authors":"Bo Wang, W. An, Yiyu Zhou","doi":"10.1109/IWISA.2009.5073082","DOIUrl":"https://doi.org/10.1109/IWISA.2009.5073082","url":null,"abstract":"In allusion to sensor management problem of continual midcourse object tracking in the space tracking and surveillance system, a novel optimized objective function was proposed according to analysis of its restriction. Furthermore, on the basis of analyzing the disadvantages of binary particle swarm optimization based sensor management, a novel method based on real-number particle swarm optimization was proposed through dimensionality reduction and position vector improvement. Ultimately, simulation about classical midcourse object tracking scenario was executed, and the performance of several methods were compared in detail. The simulation results indicated that the novel optimized objective function could schedule sensors effectively; moreover, the proposed sensor management was a more efficient method.","PeriodicalId":6327,"journal":{"name":"2009 International Workshop on Intelligent Systems and Applications","volume":"18 1 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2009-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82816105","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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