Pub Date : 2010-11-22DOI: 10.1109/CINC.2010.5643758
Yan Wu, Bing Xu, Xiao-Yue Bian
An improved PCNN model-PCNN with Positive and Negative Firing, PCNNPNF-is proposed, and also put forward a de-noising algorithm based on the time matrix of PCNNPNF. The biggest improvement is that the neuron's output of improved PCNN has three states: positive firing, negative firing and no firing, while PCNN only has two states: firing and no firing. Experimental results show that the de-noising algorithm based on PCNNPNF can quickly find the two kinds of pulse noises, remove these noises, and reserve more information than PCNN.
提出了一种改进的PCNN模型PCNNPNF- Positive and Negative Firing，并提出了一种基于PCNNPNF时间矩阵的去噪算法。最大的改进是改进后的PCNN神经元输出有正放电、负放电和不放电三种状态，而PCNN只有放电和不放电两种状态。实验结果表明，基于PCNNPNF的去噪算法能够快速发现并去除两种脉冲噪声，并且比PCNN保留更多的信息。
{"title":"An improved PCNN model and a new removing algorithm of salt and pepper noise","authors":"Yan Wu, Bing Xu, Xiao-Yue Bian","doi":"10.1109/CINC.2010.5643758","DOIUrl":"https://doi.org/10.1109/CINC.2010.5643758","url":null,"abstract":"An improved PCNN model-PCNN with Positive and Negative Firing, PCNNPNF-is proposed, and also put forward a de-noising algorithm based on the time matrix of PCNNPNF. The biggest improvement is that the neuron's output of improved PCNN has three states: positive firing, negative firing and no firing, while PCNN only has two states: firing and no firing. Experimental results show that the de-noising algorithm based on PCNNPNF can quickly find the two kinds of pulse noises, remove these noises, and reserve more information than PCNN.","PeriodicalId":227004,"journal":{"name":"2010 Second International Conference on Computational Intelligence and Natural Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2010-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115942178","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 : 2010-11-22DOI: 10.1109/CINC.2010.5643746
Guoqiang Zhang, Jun Chen
Multi-class traffic assignment problem is an extension of the classic static traffic assignment problem with user equilibrium. It provides a more correct and detailed description of traffic patterns and trends. Because of the complexity of the models for multi-class traffic assignment problem, which are usually defined by a non-monotonic cost operator, neither the uniqueness nor the stability of a feasible solution can be guaranteed and the traditional nonlinear optimization algorithms are therefore invalid. Based upon the mathematic characteristics of multiclass traffic assignment problem, genetic algorithm has been adopted for its solution. To ensue efficiency of the algorithm, the genetic operators such as crossover and mutation were designed specifically, as expressed by Equation 11, 12 and 13, so that constrains expressed by Equation 5 can be satisfied. With a test road network as an example, as shown in Figure 1, the new genetic algorithm has been proved to be very effective.
{"title":"Solving multi-class traffic assignment problem with genetic algorithm","authors":"Guoqiang Zhang, Jun Chen","doi":"10.1109/CINC.2010.5643746","DOIUrl":"https://doi.org/10.1109/CINC.2010.5643746","url":null,"abstract":"Multi-class traffic assignment problem is an extension of the classic static traffic assignment problem with user equilibrium. It provides a more correct and detailed description of traffic patterns and trends. Because of the complexity of the models for multi-class traffic assignment problem, which are usually defined by a non-monotonic cost operator, neither the uniqueness nor the stability of a feasible solution can be guaranteed and the traditional nonlinear optimization algorithms are therefore invalid. Based upon the mathematic characteristics of multiclass traffic assignment problem, genetic algorithm has been adopted for its solution. To ensue efficiency of the algorithm, the genetic operators such as crossover and mutation were designed specifically, as expressed by Equation 11, 12 and 13, so that constrains expressed by Equation 5 can be satisfied. With a test road network as an example, as shown in Figure 1, the new genetic algorithm has been proved to be very effective.","PeriodicalId":227004,"journal":{"name":"2010 Second International Conference on Computational Intelligence and Natural Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2010-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131633087","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 : 2010-11-22DOI: 10.1109/CINC.2010.5643731
Yanmin Ning, Dean Zhao, Jiajun Guan, Shichang Gong
In this paper, a new sewage flow remote monitoring system over General Packet Radio Service (GPRS) is presented, which monitors the sewage flow parameter remotely in real time. In the proposed system, GPRS network is adopted as the wireless sensor network, and the data between the slave computer and the remote terminal are transmitted via the GPRS and Internet networks. Finally in the remote terminal, the Winsock control of Visual Basic 6.0 is responsible for displaying, storing and analyzing the data of the sewage flow. The system is easy to implement and has a high degree of automation, by which the acquisition, transmission and processing of the sewage flow data can be achieved in wireless, networked and intelligent manners.
{"title":"Design of sewage flow remote monitoring system over GPRS network","authors":"Yanmin Ning, Dean Zhao, Jiajun Guan, Shichang Gong","doi":"10.1109/CINC.2010.5643731","DOIUrl":"https://doi.org/10.1109/CINC.2010.5643731","url":null,"abstract":"In this paper, a new sewage flow remote monitoring system over General Packet Radio Service (GPRS) is presented, which monitors the sewage flow parameter remotely in real time. In the proposed system, GPRS network is adopted as the wireless sensor network, and the data between the slave computer and the remote terminal are transmitted via the GPRS and Internet networks. Finally in the remote terminal, the Winsock control of Visual Basic 6.0 is responsible for displaying, storing and analyzing the data of the sewage flow. The system is easy to implement and has a high degree of automation, by which the acquisition, transmission and processing of the sewage flow data can be achieved in wireless, networked and intelligent manners.","PeriodicalId":227004,"journal":{"name":"2010 Second International Conference on Computational Intelligence and Natural Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2010-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131260959","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 : 2010-11-22DOI: 10.1109/CINC.2010.5643870
Shuhua Su, Gongxiang Chen
In order to investigate the influence of achievement goal orientation, self-efficacy and task difficulty on judgment of learning (JOL), we selected 96 senior high School students that were investigated through RJR paradigm and materials (meaningful and meaningless associated Chinese word -pairs) in this study. The results showed that: (1) Achievement goal orientation, self-efficacy and material factor had prominent influence on judgment of learning. (2) Achievement goal orientation and self-efficacy had different interactive influence on judgment of learning. (3)The testing of mediating effect indicated that self-efficacy was a mediator factor between achievement goal orientation and judgment of learning. So we draw the conclusions that achievement goal orientation, self-efficacy and task difficulty affect JOL.
{"title":"The influence of achievement goal orientation, self-efficacy and task difficulty on JOL","authors":"Shuhua Su, Gongxiang Chen","doi":"10.1109/CINC.2010.5643870","DOIUrl":"https://doi.org/10.1109/CINC.2010.5643870","url":null,"abstract":"In order to investigate the influence of achievement goal orientation, self-efficacy and task difficulty on judgment of learning (JOL), we selected 96 senior high School students that were investigated through RJR paradigm and materials (meaningful and meaningless associated Chinese word -pairs) in this study. The results showed that: (1) Achievement goal orientation, self-efficacy and material factor had prominent influence on judgment of learning. (2) Achievement goal orientation and self-efficacy had different interactive influence on judgment of learning. (3)The testing of mediating effect indicated that self-efficacy was a mediator factor between achievement goal orientation and judgment of learning. So we draw the conclusions that achievement goal orientation, self-efficacy and task difficulty affect JOL.","PeriodicalId":227004,"journal":{"name":"2010 Second International Conference on Computational Intelligence and Natural Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2010-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123684534","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 : 2010-11-22DOI: 10.1109/CINC.2010.5643737
Chang-sheng Zhu, Hongmei Huang, Yuan Yuan, Qing-rong Wang
In this work,we set up public transit planning model by analysising of vehicle dispatching and taking both interest of bus company and passenger into consideration. using the improved genetic simulated annealing algorithm(the improved GA-SA) to carry out optimization for public transit dispatching model,and overcomes the problems such as evolution is slow,precocious, local optimal solution and so on, it can find the approximate optimum solution, reliably, from the huge search space of scheduling optimization problem. intelligent scheduling optimization problem in the great search space to find reliable optimal solution or approximate optimal solution. Finally,we use MATLAB to carry on simulation experiment. the results show that the improved GA-SA has higher efficiency than traditional GA.
{"title":"The research in public transit scheduling based on the improved genetic simulated annealing algorithm","authors":"Chang-sheng Zhu, Hongmei Huang, Yuan Yuan, Qing-rong Wang","doi":"10.1109/CINC.2010.5643737","DOIUrl":"https://doi.org/10.1109/CINC.2010.5643737","url":null,"abstract":"In this work,we set up public transit planning model by analysising of vehicle dispatching and taking both interest of bus company and passenger into consideration. using the improved genetic simulated annealing algorithm(the improved GA-SA) to carry out optimization for public transit dispatching model,and overcomes the problems such as evolution is slow,precocious, local optimal solution and so on, it can find the approximate optimum solution, reliably, from the huge search space of scheduling optimization problem. intelligent scheduling optimization problem in the great search space to find reliable optimal solution or approximate optimal solution. Finally,we use MATLAB to carry on simulation experiment. the results show that the improved GA-SA has higher efficiency than traditional GA.","PeriodicalId":227004,"journal":{"name":"2010 Second International Conference on Computational Intelligence and Natural Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2010-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123182161","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 : 2010-11-22DOI: 10.1109/CINC.2010.5643898
J. Qian, Jianguo Zheng, Chaoqun Zhang
Traditionally, some common algorithms to optimize the integration of logistics resource are linear programming, dynamic programming, and etc., however, these algorithms can't well solve many complex optimization issues, especially nonlinear issues, because of the continuous growth of issue complexity. On the contrary, intelligent computing technology has many advantages in solving complex, nonlinear and multi-objective optimization issue. But, how to build intelligent logistics management system based on intelligent computing technology has become a challenge. This paper, focusing on the function and system structure of intelligent management platform, presents the design of intelligent logistics management system based on Global Positioning System (GPS), Geographic Information System (GIS), and intelligent computing. Finally, a sample model of using quantum genetic intelligent algorithm to solve transportation problem in the intelligent logistics management system is given.
{"title":"The intelligent logistics management system based on intelligent computing","authors":"J. Qian, Jianguo Zheng, Chaoqun Zhang","doi":"10.1109/CINC.2010.5643898","DOIUrl":"https://doi.org/10.1109/CINC.2010.5643898","url":null,"abstract":"Traditionally, some common algorithms to optimize the integration of logistics resource are linear programming, dynamic programming, and etc., however, these algorithms can't well solve many complex optimization issues, especially nonlinear issues, because of the continuous growth of issue complexity. On the contrary, intelligent computing technology has many advantages in solving complex, nonlinear and multi-objective optimization issue. But, how to build intelligent logistics management system based on intelligent computing technology has become a challenge. This paper, focusing on the function and system structure of intelligent management platform, presents the design of intelligent logistics management system based on Global Positioning System (GPS), Geographic Information System (GIS), and intelligent computing. Finally, a sample model of using quantum genetic intelligent algorithm to solve transportation problem in the intelligent logistics management system is given.","PeriodicalId":227004,"journal":{"name":"2010 Second International Conference on Computational Intelligence and Natural Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2010-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116894102","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 : 2010-11-22DOI: 10.1109/CINC.2010.5643812
Xiaoping Tian, Sishijiu Dong, Yu Han
We analyze the performance of spread spectrum (SS) communication system in fading enviornment and interference based on simulation platform. Modules of the spread spectrum system and environment with interference and fading are simulated and modeled. Monte Carlo simulation experiments are done based on the spread spectrum communication simulation platform. Then the BER performance of spread spectrum communication simulation system over interference and fading channels are obtained from the simulation results. Theory analysis and simulation experiments show that SS technology can effectively combat interference and are adaptive to the fading environment.
{"title":"Performance analysis of spread spectrum communication system in fading enviornment and Interference","authors":"Xiaoping Tian, Sishijiu Dong, Yu Han","doi":"10.1109/CINC.2010.5643812","DOIUrl":"https://doi.org/10.1109/CINC.2010.5643812","url":null,"abstract":"We analyze the performance of spread spectrum (SS) communication system in fading enviornment and interference based on simulation platform. Modules of the spread spectrum system and environment with interference and fading are simulated and modeled. Monte Carlo simulation experiments are done based on the spread spectrum communication simulation platform. Then the BER performance of spread spectrum communication simulation system over interference and fading channels are obtained from the simulation results. Theory analysis and simulation experiments show that SS technology can effectively combat interference and are adaptive to the fading environment.","PeriodicalId":227004,"journal":{"name":"2010 Second International Conference on Computational Intelligence and Natural Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2010-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114100323","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 : 2010-11-22DOI: 10.1109/CINC.2010.5643839
Heng Fui Liau, D. Isa
This paper proposes a feature selection method that aims to select an optimal feature subset to representing facial image from the point of view of minimizing the total error rate (TER) of the system. In this proposed approach, the genuine user score distribution and the imposter score distribution are modeled based on a Parzen-window density estimation to enable the direct estimation of total error rate (TER) as reflected by the area under the curve of the overlapping region of both distributions. Particle swarm optimization (PSO) is employed to search for feature subsets which are extracted from discrete cosine transform or principal component analysis that gives minimum TER and in the meantime to reduce the dimensionality of the feature set thereby reducing processing time.
{"title":"Feature selection method for facial representation using parzen-window density estimation","authors":"Heng Fui Liau, D. Isa","doi":"10.1109/CINC.2010.5643839","DOIUrl":"https://doi.org/10.1109/CINC.2010.5643839","url":null,"abstract":"This paper proposes a feature selection method that aims to select an optimal feature subset to representing facial image from the point of view of minimizing the total error rate (TER) of the system. In this proposed approach, the genuine user score distribution and the imposter score distribution are modeled based on a Parzen-window density estimation to enable the direct estimation of total error rate (TER) as reflected by the area under the curve of the overlapping region of both distributions. Particle swarm optimization (PSO) is employed to search for feature subsets which are extracted from discrete cosine transform or principal component analysis that gives minimum TER and in the meantime to reduce the dimensionality of the feature set thereby reducing processing time.","PeriodicalId":227004,"journal":{"name":"2010 Second International Conference on Computational Intelligence and Natural Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2010-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114580388","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 : 2010-11-22DOI: 10.1109/CINC.2010.5643828
Tong Wang, Qinghua Huang, Lihua Hu
The subcellular location of a protein is closely correlated to its function. Facing the deluge of protein sequences generated in the post-genomic age, it is necessary to develop useful machine learning tools to identify the protein subcellular localization. DR (Dimensional Reduction) method is one of most famous machine learning tools. Some researchers have begun to explore DR method for computer vision problems such as face recognition, few such attempts have been made for classification of high-dimensional protein data sets. In this paper, DR method is employed to reduce the size of the features space. Comparison between linear DR methods (PCA and LDA) and nonlinear DR methods (KPCA and KLDA) is performed to predict subcellular localization of nuclear proteins. Experimental results thus obtained are quite encouraging, which indicate that the DR method is used effectively to deal with this complicated problem of viral proteins subcellular localization prediction. The overall jackknife success rate with KLDA is the highest relative to the other DR methods.
{"title":"Identifying nuclear protein subcellular localization using feature dimension reduction method","authors":"Tong Wang, Qinghua Huang, Lihua Hu","doi":"10.1109/CINC.2010.5643828","DOIUrl":"https://doi.org/10.1109/CINC.2010.5643828","url":null,"abstract":"The subcellular location of a protein is closely correlated to its function. Facing the deluge of protein sequences generated in the post-genomic age, it is necessary to develop useful machine learning tools to identify the protein subcellular localization. DR (Dimensional Reduction) method is one of most famous machine learning tools. Some researchers have begun to explore DR method for computer vision problems such as face recognition, few such attempts have been made for classification of high-dimensional protein data sets. In this paper, DR method is employed to reduce the size of the features space. Comparison between linear DR methods (PCA and LDA) and nonlinear DR methods (KPCA and KLDA) is performed to predict subcellular localization of nuclear proteins. Experimental results thus obtained are quite encouraging, which indicate that the DR method is used effectively to deal with this complicated problem of viral proteins subcellular localization prediction. The overall jackknife success rate with KLDA is the highest relative to the other DR methods.","PeriodicalId":227004,"journal":{"name":"2010 Second International Conference on Computational Intelligence and Natural Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2010-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114734281","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 : 2010-11-22DOI: 10.1109/CINC.2010.5643723
Bo Zhang
In this paper, a class of modified conjugate gradient methods are proposed, which have the following attractive properties: (1) the step length is determined by a formula; (2) the iterative direction is always a sufficient descent direction without utilizing the line search. Under the boundedness of the level set and the Lipschitz continuity of the underlying function, the proposed methods are global convergent. Some numerical results are given to illustrate the effectiveness of the proposed methods.
{"title":"Convergence of modified conjugate gradient methods without line search","authors":"Bo Zhang","doi":"10.1109/CINC.2010.5643723","DOIUrl":"https://doi.org/10.1109/CINC.2010.5643723","url":null,"abstract":"In this paper, a class of modified conjugate gradient methods are proposed, which have the following attractive properties: (1) the step length is determined by a formula; (2) the iterative direction is always a sufficient descent direction without utilizing the line search. Under the boundedness of the level set and the Lipschitz continuity of the underlying function, the proposed methods are global convergent. Some numerical results are given to illustrate the effectiveness of the proposed methods.","PeriodicalId":227004,"journal":{"name":"2010 Second International Conference on Computational Intelligence and Natural Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2010-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123857297","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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