International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications最新文献
Pub Date : 2012-05-29DOI: 10.1109/ICNC.2012.6234563
Lin-xiu Sha, Yuyao He
The current quantum evolution algorithms have slow convergence rate and poor robustness. In order to overcome the two shortages, a novel self-adaptive quantum genetic algorithm is proposed. Firstly, the new algorithm adopts an encoding method which is based on the Bloch spherical coordinates. Secondly, in the process of searching the optimal solution, a self-adaptive factor is introduced to reflect the relative change rates which are relative to the difference of the best individual's objective fitness between the parent generation and the child generation. The convergence rate and direction of the algorithm can be improved by adjusting the factor. The rules of updating the rotation angle and are constructed. Finally, using hadamard gate of the quantum in the mutation strategy, it can enhance the diversity of population. The simulation results of the optimizing problem of the multidimensional complex functions show that the new algorithm has not only avoided effectively the premature and improved the convergence rate, but also boosted strikingly efficiency and stability robustness of the algorithm.
{"title":"A novel self-adaptive quantum genetic algorithm","authors":"Lin-xiu Sha, Yuyao He","doi":"10.1109/ICNC.2012.6234563","DOIUrl":"https://doi.org/10.1109/ICNC.2012.6234563","url":null,"abstract":"The current quantum evolution algorithms have slow convergence rate and poor robustness. In order to overcome the two shortages, a novel self-adaptive quantum genetic algorithm is proposed. Firstly, the new algorithm adopts an encoding method which is based on the Bloch spherical coordinates. Secondly, in the process of searching the optimal solution, a self-adaptive factor is introduced to reflect the relative change rates which are relative to the difference of the best individual's objective fitness between the parent generation and the child generation. The convergence rate and direction of the algorithm can be improved by adjusting the factor. The rules of updating the rotation angle and are constructed. Finally, using hadamard gate of the quantum in the mutation strategy, it can enhance the diversity of population. The simulation results of the optimizing problem of the multidimensional complex functions show that the new algorithm has not only avoided effectively the premature and improved the convergence rate, but also boosted strikingly efficiency and stability robustness of the algorithm.","PeriodicalId":87274,"journal":{"name":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","volume":"40 1","pages":"618-621"},"PeriodicalIF":0.0,"publicationDate":"2012-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87246857","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 : 2012-05-29DOI: 10.1109/ICNC.2012.6234595
Zongbin Ye, Wei Jing, Chen Xia
A nonlinear controller based on single neuron adaptive control has been developed for the doubly-fed induction motor, which implement the self optimizing control for the parameters of speed loop and gain an excellent torque tracking control. The strategy and stability of the designed controller are deduced and verified by experiments on a platform. The results of the experiment indicate that the controller can realize self optimizing control for the parameters of speed loop and obtain fine dynamic and static performance.
{"title":"Single neuron adaptive controller for doubly-fed motor drive system","authors":"Zongbin Ye, Wei Jing, Chen Xia","doi":"10.1109/ICNC.2012.6234595","DOIUrl":"https://doi.org/10.1109/ICNC.2012.6234595","url":null,"abstract":"A nonlinear controller based on single neuron adaptive control has been developed for the doubly-fed induction motor, which implement the self optimizing control for the parameters of speed loop and gain an excellent torque tracking control. The strategy and stability of the designed controller are deduced and verified by experiments on a platform. The results of the experiment indicate that the controller can realize self optimizing control for the parameters of speed loop and obtain fine dynamic and static performance.","PeriodicalId":87274,"journal":{"name":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","volume":"21 1","pages":"461-465"},"PeriodicalIF":0.0,"publicationDate":"2012-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86285997","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 : 2012-05-29DOI: 10.1109/ICNC.2012.6234652
H. Ge, Liang Sun
Identification and control of nonlinear dynamic system plays an important role in many applications. In this paper, a novel bacterial foraging strategy-based Elman neural network is proposed for identifying and controlling nonlinear systems. We first present a learning algorithm for dynamic recurrent networks based on a bacterial foraging strategy oriented by quorum sensing and communication. The proposed algorithm computes concurrently both the weights, initial inputs of the context units and self-feedback coefficient of the Elman network. Thereafter, we introduce and discuss a novel control method based on the proposed algorithm. More specifically, a dynamic identifier is constructed to perform speed identification and a controller is designed to perform speed control for Ultrasonic Motors (USM). Numerical experiments show that the identifier and controller can both achieve higher convergence precision and speed. Besides, a preliminary examination on a random perturbation also shows the robust characteristics of the proposed models.
{"title":"A bacterial foraging strategy-based recurrent neural network for identifying and controlling nonlinear systems","authors":"H. Ge, Liang Sun","doi":"10.1109/ICNC.2012.6234652","DOIUrl":"https://doi.org/10.1109/ICNC.2012.6234652","url":null,"abstract":"Identification and control of nonlinear dynamic system plays an important role in many applications. In this paper, a novel bacterial foraging strategy-based Elman neural network is proposed for identifying and controlling nonlinear systems. We first present a learning algorithm for dynamic recurrent networks based on a bacterial foraging strategy oriented by quorum sensing and communication. The proposed algorithm computes concurrently both the weights, initial inputs of the context units and self-feedback coefficient of the Elman network. Thereafter, we introduce and discuss a novel control method based on the proposed algorithm. More specifically, a dynamic identifier is constructed to perform speed identification and a controller is designed to perform speed control for Ultrasonic Motors (USM). Numerical experiments show that the identifier and controller can both achieve higher convergence precision and speed. Besides, a preliminary examination on a random perturbation also shows the robust characteristics of the proposed models.","PeriodicalId":87274,"journal":{"name":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","volume":"19 1","pages":"1127-1131"},"PeriodicalIF":0.0,"publicationDate":"2012-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77710681","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 : 2012-05-29DOI: 10.1109/ICNC.2012.6234751
Jingyi Zhang, Lan Wang, M. Zhu, Yuan Zhu, Qing Yang
A combined approach based on wavelet packet energy and probabilistic neural network (WPE-PNN) is presented to diagnose faults in the rolling bearing vibration signal research. Firstly wavelet packet is used to decompose rolling bearing vibration signals into three-layer, and extract the energy characteristics. Then PNN is proposed to diagnose faults. Finally, remote fault diagnosis is realized by virtual instrument technology. The proposed method can provide an accepted degree of accuracy in fault classification under different fault conditions and can be operated remotely from another station connected to the server via the World Wide Web.
{"title":"Fault diagnosis based on wavelet packet energy and PNN analysis method for rolling bearing","authors":"Jingyi Zhang, Lan Wang, M. Zhu, Yuan Zhu, Qing Yang","doi":"10.1109/ICNC.2012.6234751","DOIUrl":"https://doi.org/10.1109/ICNC.2012.6234751","url":null,"abstract":"A combined approach based on wavelet packet energy and probabilistic neural network (WPE-PNN) is presented to diagnose faults in the rolling bearing vibration signal research. Firstly wavelet packet is used to decompose rolling bearing vibration signals into three-layer, and extract the energy characteristics. Then PNN is proposed to diagnose faults. Finally, remote fault diagnosis is realized by virtual instrument technology. The proposed method can provide an accepted degree of accuracy in fault classification under different fault conditions and can be operated remotely from another station connected to the server via the World Wide Web.","PeriodicalId":87274,"journal":{"name":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","volume":"124 1","pages":"229-232"},"PeriodicalIF":0.0,"publicationDate":"2012-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83978203","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 : 2012-05-29DOI: 10.1109/ICNC.2012.6234512
Min Fang, WenKe Niu, Xiaosong Zhang
The partition of a pattern space as the view of a cell space is a uniform partition, it is difficult to adapt to the needs of spatial non-uniform partition. In this paper, a cellular automaton classifier with a tree structure is constructed by combing with the CART algorithm. The construction method of the characteristic matrix of the multiple attractor cellular automata is studied based on the particle swarm optimization method, and this method can build the nodes of the multiple attractor cellular automata. This kind of classifier can solve the non-uniform partition problem and obtain a good classification performance while using a pseudo-exhaustive field with less bits. The experiment results show that our algorithm is more accurate than those obtained through the multiple attractor cellular automata.
{"title":"Research on the classifier with the tree frame based on multiple attractor cellular automaton","authors":"Min Fang, WenKe Niu, Xiaosong Zhang","doi":"10.1109/ICNC.2012.6234512","DOIUrl":"https://doi.org/10.1109/ICNC.2012.6234512","url":null,"abstract":"The partition of a pattern space as the view of a cell space is a uniform partition, it is difficult to adapt to the needs of spatial non-uniform partition. In this paper, a cellular automaton classifier with a tree structure is constructed by combing with the CART algorithm. The construction method of the characteristic matrix of the multiple attractor cellular automata is studied based on the particle swarm optimization method, and this method can build the nodes of the multiple attractor cellular automata. This kind of classifier can solve the non-uniform partition problem and obtain a good classification performance while using a pseudo-exhaustive field with less bits. The experiment results show that our algorithm is more accurate than those obtained through the multiple attractor cellular automata.","PeriodicalId":87274,"journal":{"name":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","volume":"6 1","pages":"1079-1083"},"PeriodicalIF":0.0,"publicationDate":"2012-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78286514","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 : 2012-05-29DOI: 10.1109/ICNC.2012.6234774
Jianhua Guo, Haidong Yang
Negative Selection Algorithm (NSA) is an artificial immune system for anomaly detection. Three weaknesses in NSA are the exponential cost of generating detectors, the difficulty to set the matching threshold, and the deviation between the real and the expected miss detection rate. To improve these weaknesses, a new Negative Selection Algorithm Integrated with Immune Network theory (NSA-IN) was proposed. A matching rule with variable threshold was defined, and clonal selection was adopted to rapidly mature the detectors with low similarity to self bodies and self-adaptively get the matching threshold of detectors, and immune network theory was adopted to optimize the distribution of mature detectors and improve detection rate. Experiments show that, NSA-IN can automatically set the matching threshold, and is the linear cost of generating detectors, and reduces the deviation between the real and the expected miss detection rate. In RFID anomaly detection case, the average miss detection rate of NSA-IN is 0.098, and is lower than that of NSA 0.234.
{"title":"A Negative Selection Algorithm Integrated with Immune Network Theory","authors":"Jianhua Guo, Haidong Yang","doi":"10.1109/ICNC.2012.6234774","DOIUrl":"https://doi.org/10.1109/ICNC.2012.6234774","url":null,"abstract":"Negative Selection Algorithm (NSA) is an artificial immune system for anomaly detection. Three weaknesses in NSA are the exponential cost of generating detectors, the difficulty to set the matching threshold, and the deviation between the real and the expected miss detection rate. To improve these weaknesses, a new Negative Selection Algorithm Integrated with Immune Network theory (NSA-IN) was proposed. A matching rule with variable threshold was defined, and clonal selection was adopted to rapidly mature the detectors with low similarity to self bodies and self-adaptively get the matching threshold of detectors, and immune network theory was adopted to optimize the distribution of mature detectors and improve detection rate. Experiments show that, NSA-IN can automatically set the matching threshold, and is the linear cost of generating detectors, and reduces the deviation between the real and the expected miss detection rate. In RFID anomaly detection case, the average miss detection rate of NSA-IN is 0.098, and is lower than that of NSA 0.234.","PeriodicalId":87274,"journal":{"name":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","volume":"11 1","pages":"859-863"},"PeriodicalIF":0.0,"publicationDate":"2012-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86256276","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 : 2012-05-29DOI: 10.1109/ICNC.2012.6234662
Yong Zhao, Hong Ye, Zheng-sheng Kang, Song-shan Shi, Lin Zhou
In order to the recognition of the train wheel tread damages, the pattern recognition method of the train wheel tread damages based on PSO-RBFNN was developed. The algorithm uses PSO-RBFNN algorithm to optimize center and spread of RBFNN, the connection weight value is sovled by least squares method. Compared with the traditional RBFNN,BP and GA-RBFNN, the experiment results show that the recognition rate of testing samples is higher than the traditional RBFNN, BP and GA-RBFNN, the evolutional generations of PSO-RBFNN algorithm were less than RBFNN, BP and GA-RBFNN.
{"title":"The recognition of train wheel tread damages based on PSO-RBFNN algorithm","authors":"Yong Zhao, Hong Ye, Zheng-sheng Kang, Song-shan Shi, Lin Zhou","doi":"10.1109/ICNC.2012.6234662","DOIUrl":"https://doi.org/10.1109/ICNC.2012.6234662","url":null,"abstract":"In order to the recognition of the train wheel tread damages, the pattern recognition method of the train wheel tread damages based on PSO-RBFNN was developed. The algorithm uses PSO-RBFNN algorithm to optimize center and spread of RBFNN, the connection weight value is sovled by least squares method. Compared with the traditional RBFNN,BP and GA-RBFNN, the experiment results show that the recognition rate of testing samples is higher than the traditional RBFNN, BP and GA-RBFNN, the evolutional generations of PSO-RBFNN algorithm were less than RBFNN, BP and GA-RBFNN.","PeriodicalId":87274,"journal":{"name":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","volume":"70 1","pages":"1093-1095"},"PeriodicalIF":0.0,"publicationDate":"2012-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81804088","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 : 2012-05-29DOI: 10.1109/ICNC.2012.6234619
Yang Pan, Jianlin Qiu, Li Chen, Xiang Gu, Jianping Chen, Yanyun Chen
In order to take full advantage of multi-core resources to enhance the parallel performance, we study the architecture of multi-core processor and point out that the heterogeneous multi-core processor is the mainstream of development. With Amdahl's law, only by developing a new parallel programming model can solve the contradiction between traditional programming model and multi-core parallel structure.
{"title":"The research of multi-core parallel technology","authors":"Yang Pan, Jianlin Qiu, Li Chen, Xiang Gu, Jianping Chen, Yanyun Chen","doi":"10.1109/ICNC.2012.6234619","DOIUrl":"https://doi.org/10.1109/ICNC.2012.6234619","url":null,"abstract":"In order to take full advantage of multi-core resources to enhance the parallel performance, we study the architecture of multi-core processor and point out that the heterogeneous multi-core processor is the mainstream of development. With Amdahl's law, only by developing a new parallel programming model can solve the contradiction between traditional programming model and multi-core parallel structure.","PeriodicalId":87274,"journal":{"name":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","volume":"54 27","pages":"1056-1059"},"PeriodicalIF":0.0,"publicationDate":"2012-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/ICNC.2012.6234619","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72366885","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 : 2012-05-29DOI: 10.1109/ICNC.2012.6234543
C. Kang, Wentao Fan, Xin-hua Zhang, Jun Li
Direction of arrival(DOA) estimation is the base of the underwater target orientation, tracking. Based on the characteristic of the array manifold can be estimated by complex blind source separation using the singular value decomposition, a new kind of model and method for DOA estimation is proposed using the directivity patterns of the blind source separation demixing matrix. Its efficiency and stability was tested by simulation data and recorded data in real sea. Results show that it can complete the real-time estimation of the target direction. And it is superior to the minimum variance distortionless response(MVDR) method and the method proposed in relevant literatures, it can obviously improves the detection capability of the sonar system for the faint target signal obviously.
{"title":"A kind of method for direction of arrival estimation based on blind source separation demixing matrix","authors":"C. Kang, Wentao Fan, Xin-hua Zhang, Jun Li","doi":"10.1109/ICNC.2012.6234543","DOIUrl":"https://doi.org/10.1109/ICNC.2012.6234543","url":null,"abstract":"Direction of arrival(DOA) estimation is the base of the underwater target orientation, tracking. Based on the characteristic of the array manifold can be estimated by complex blind source separation using the singular value decomposition, a new kind of model and method for DOA estimation is proposed using the directivity patterns of the blind source separation demixing matrix. Its efficiency and stability was tested by simulation data and recorded data in real sea. Results show that it can complete the real-time estimation of the target direction. And it is superior to the minimum variance distortionless response(MVDR) method and the method proposed in relevant literatures, it can obviously improves the detection capability of the sonar system for the faint target signal obviously.","PeriodicalId":87274,"journal":{"name":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","volume":"18 1","pages":"134-137"},"PeriodicalIF":0.0,"publicationDate":"2012-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73324457","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 : 2012-05-29DOI: 10.1109/ICNC.2012.6234729
De-gang Ji, Dong-mei Huang
Vehicle Routing Problem(VRP) is an important problem in logistic system. Because of its NP-hard property, it is difficult to get the optimal solution when the constrains are more. Aiming at the problem of logistics distribution vehicle routing optimization, this paper provide a composite algorithm based on the K-means clustering and the Artificial Fish-Swarm Algorithm for the vehicle routing optimization(KMAFA). The results indicate that the algorithm can reduce the input of the algorithm and improve the converging speed. The computational result shows that the results of composite algorithm for VRP are competitive.
{"title":"A research based on K-means clustering and Artificial Fish-Swarm Algorithm for the Vehicle Routing Optimization","authors":"De-gang Ji, Dong-mei Huang","doi":"10.1109/ICNC.2012.6234729","DOIUrl":"https://doi.org/10.1109/ICNC.2012.6234729","url":null,"abstract":"Vehicle Routing Problem(VRP) is an important problem in logistic system. Because of its NP-hard property, it is difficult to get the optimal solution when the constrains are more. Aiming at the problem of logistics distribution vehicle routing optimization, this paper provide a composite algorithm based on the K-means clustering and the Artificial Fish-Swarm Algorithm for the vehicle routing optimization(KMAFA). The results indicate that the algorithm can reduce the input of the algorithm and improve the converging speed. The computational result shows that the results of composite algorithm for VRP are competitive.","PeriodicalId":87274,"journal":{"name":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","volume":"136 1","pages":"1141-1145"},"PeriodicalIF":0.0,"publicationDate":"2012-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72682653","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}
International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications
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