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2009 Fifth International Conference on Natural Computation最新文献

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New Results on Exponential Convergence of Globally Projected Dynamic Systems 全局投影动态系统指数收敛的新结果
2009 Fifth International Conference on Natural Computation Pub Date : 2009-08-14 DOI: 10.1109/ICNC.2009.226
Lili Du
{"title":"New Results on Exponential Convergence of Globally Projected Dynamic Systems","authors":"Lili Du","doi":"10.1109/ICNC.2009.226","DOIUrl":"https://doi.org/10.1109/ICNC.2009.226","url":null,"abstract":"This paper further analyzes and improves the exponential convergence of the dynamic system proposed by Friesz et al., whose equilibria solve variational inequalities. Four sufficient conditions are provided to ensure the exponential convergence of this system. Meanwhile this system is also proved to be stable and convergent under the weaker pseudo-monotonicity of the mapping. Theoretical analysis and illustrative examples show that some obtained results improve the existing ones.","PeriodicalId":235382,"journal":{"name":"2009 Fifth International Conference on Natural Computation","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121357349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Knowledge Migration Based Multi-population Cultural Algorithm 基于知识迁移的多种群文化算法
2009 Fifth International Conference on Natural Computation Pub Date : 2009-08-14 DOI: 10.1109/ICNC.2009.597
Yi-nan Guo, Yuan-yuan Cao, Yong Lin, Hui Wang
{"title":"Knowledge Migration Based Multi-population Cultural Algorithm","authors":"Yi-nan Guo, Yuan-yuan Cao, Yong Lin, Hui Wang","doi":"10.1109/ICNC.2009.597","DOIUrl":"https://doi.org/10.1109/ICNC.2009.597","url":null,"abstract":"In existing multi-population cultural algorithms, information are exchanged among sub-populations by individuals, which limits the evolution performance. So a novel multi-population cultural algorithm adopting knowledge migration is proposed. Implicit knowledge extracted from each sub-population reflects the information about dominant search space. By migrating the knowledge among sub-populations at the constant interval, the algorithm realizes more effective interaction with less communication cost. Taken benchmark functions as the examples, simulation results indicate that the algorithm can effectively improve the speed of convergence and overcome premature convergence.","PeriodicalId":235382,"journal":{"name":"2009 Fifth International Conference on Natural Computation","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127330032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 8
The Neural Network Proportion Integral Differential Controller and the Application on Mill Hydraulic Pressure Automatic Gauge Control System 神经网络比例积分微分控制器及其在轧机液压自动仪表控制系统中的应用
2009 Fifth International Conference on Natural Computation Pub Date : 2009-08-14 DOI: 10.1109/ICNC.2009.517
Xiaoye Wang, Hua Zhang, Yingyuan Xiao, Degan Zhang
{"title":"The Neural Network Proportion Integral Differential Controller and the Application on Mill Hydraulic Pressure Automatic Gauge Control System","authors":"Xiaoye Wang, Hua Zhang, Yingyuan Xiao, Degan Zhang","doi":"10.1109/ICNC.2009.517","DOIUrl":"https://doi.org/10.1109/ICNC.2009.517","url":null,"abstract":"This paper presents a neural network proportion integral differential (PID) controller for automatic gauge control (AGC) System of rolling mill, it is an high non-linear and time-varying system. The traditional PID controller has the invariable parameters. However in the actual factory, the environment of the controlled object is often changed. If the three parameters of PID controller can’t adjusted adaptively, the controller will have a badly control effect. The neural network can adjust the three parameter based on the control error. If the control error becomes zero, the parameter didn’t adjust too. The simulation shows that neural network PID controller has good dynamic quality. The control system has short response time, small over modulation, highly steady state behavior and robustness comparing with the traditional PID controller.","PeriodicalId":235382,"journal":{"name":"2009 Fifth International Conference on Natural Computation","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124733854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Deformation Prediction of Transmission Pole Foundation by Using Improved BP Neural Network 基于改进BP神经网络的输电杆基础变形预测
2009 Fifth International Conference on Natural Computation Pub Date : 2009-08-14 DOI: 10.1109/ICNC.2009.474
Yong Zhang, Yun-feng Zhao
{"title":"Deformation Prediction of Transmission Pole Foundation by Using Improved BP Neural Network","authors":"Yong Zhang, Yun-feng Zhao","doi":"10.1109/ICNC.2009.474","DOIUrl":"https://doi.org/10.1109/ICNC.2009.474","url":null,"abstract":"Based on the field survey data of the goaf along the UHV path and by including the main geological and mining factors, the stability of UHV transmission pole foundation via Shanxi goaf have been analyzed in details. Using BP artificial neural network method, the paper set up the prediction model of subsidence deformation of pole foundation above the goaf through experiment and study of the data samples. Levenberg-Marquardt algorithm was applied in order to achieve better results. It is concluded that by using BP neural network model, predicting pole foundation stability of the goaf is convenient, reliable, and more applicable.","PeriodicalId":235382,"journal":{"name":"2009 Fifth International Conference on Natural Computation","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124917206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Linear Programming Model of Sewer Networks Based on Topography-Geomorphic 基于地形地貌的下水道网络线性规划模型
2009 Fifth International Conference on Natural Computation Pub Date : 2009-08-14 DOI: 10.1109/ICNC.2009.159
Chen Jun-quan, Yan Yuanming
{"title":"Linear Programming Model of Sewer Networks Based on Topography-Geomorphic","authors":"Chen Jun-quan, Yan Yuanming","doi":"10.1109/ICNC.2009.159","DOIUrl":"https://doi.org/10.1109/ICNC.2009.159","url":null,"abstract":"This paper discusses the role of Topography-Geomorphic in optimal design of the sewer networks, takes the coordinate parameters charactering Topography-Geomorphic as constraint condition, introduces the new economy parameter closely related to the coordinates and engineered meaning, gives formulas and assignment principle, and builts the linear programming model of sewer networks optimal design based on Topography-Geomorphic.","PeriodicalId":235382,"journal":{"name":"2009 Fifth International Conference on Natural Computation","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125103769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Cooperative Spectrum Sensing Algorithm Based on Date Fusion under Bandwidth Constraints 带宽约束下基于数据融合的协同频谱感知算法
2009 Fifth International Conference on Natural Computation Pub Date : 2009-08-14 DOI: 10.1109/ICNC.2009.480
Bian Li, Zhu Qi
{"title":"Cooperative Spectrum Sensing Algorithm Based on Date Fusion under Bandwidth Constraints","authors":"Bian Li, Zhu Qi","doi":"10.1109/ICNC.2009.480","DOIUrl":"https://doi.org/10.1109/ICNC.2009.480","url":null,"abstract":"Cooperative spectrum sensing enables a Cognitive Radio (CR) networks to reliably detect primary users and avoid causing interference to primary user’s communications, and data fusion technique is a key component of it. However, when the number of CR users tends to be large, the bandwidth for reporting their sensing results to the fusion center will be very enormous. In this paper, censoring schemes based on “AND” rule and “OR” rule for cooperative spectrum sensing are proposed to decrease the average number of sensing bits to the fusion center. Consequently, the bandwidth is saved efficiently. The performance of spectrum sensing is investigated for perfect reporting channels, imperfect reporting channels with same bit error and imperfect reporting channels with different bit error, and the close formulations are presented. Simulation results show that the average number of sensing bits decreases greatly at the expense of a little sensing performance loss using these two methods, and they both have their own advantages.","PeriodicalId":235382,"journal":{"name":"2009 Fifth International Conference on Natural Computation","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126037722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Exponential Stability of Stochastic Hopfield Neural Networks with Delays and Markovian Switching 时滞和马尔可夫切换随机Hopfield神经网络的指数稳定性
2009 Fifth International Conference on Natural Computation Pub Date : 2009-08-14 DOI: 10.1109/ICNC.2009.231
Li Wan
{"title":"Exponential Stability of Stochastic Hopfield Neural Networks with Delays and Markovian Switching","authors":"Li Wan","doi":"10.1109/ICNC.2009.231","DOIUrl":"https://doi.org/10.1109/ICNC.2009.231","url":null,"abstract":"The exponential stability for stochastic Hopfield neural networks with Markovian switching and delays is considered. The sufficient conditions are derived to guarantee the almost surely exponential stability and mean square exponential stability of a trivial solution.","PeriodicalId":235382,"journal":{"name":"2009 Fifth International Conference on Natural Computation","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126080131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Evolutionary Swarm Optimization Algorithm for Numerical Function Optimization 数值函数优化的进化群算法
2009 Fifth International Conference on Natural Computation Pub Date : 2009-08-14 DOI: 10.1109/ICNC.2009.79
Haiyan Quan, Xinling Shi
{"title":"Evolutionary Swarm Optimization Algorithm for Numerical Function Optimization","authors":"Haiyan Quan, Xinling Shi","doi":"10.1109/ICNC.2009.79","DOIUrl":"https://doi.org/10.1109/ICNC.2009.79","url":null,"abstract":"The paper introduces an evolutionary swarm model (ESM), based on the model, an evolutionary swarm algorithm (ESA) is designed out using five elements. In this work, the performance of ESA is tested with 5 multivariable benchmark functions, and compared with the other optimization algorithms. The simulation results show that the algorithm has an excellent performance in the global optimization, and can be efficiently employed to solve the optimization problem for the multimodal function with high dimensionality.","PeriodicalId":235382,"journal":{"name":"2009 Fifth International Conference on Natural Computation","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123279963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Neurocognitive Perception Process: A Case Study 神经认知知觉过程:个案研究
2009 Fifth International Conference on Natural Computation Pub Date : 2009-08-14 DOI: 10.1109/ICNC.2009.104
Zili Chen, Nana Jin, J. Webster
{"title":"Neurocognitive Perception Process: A Case Study","authors":"Zili Chen, Nana Jin, J. Webster","doi":"10.1109/ICNC.2009.104","DOIUrl":"https://doi.org/10.1109/ICNC.2009.104","url":null,"abstract":"This paper explores the relevance theory’s account for the perception of an utterance, and attempts to offer a neurophysiological justification for some key hypotheses in RT. Meanwhile a crucial proposal for neurocognitive understanding of language perception is brought forward.","PeriodicalId":235382,"journal":{"name":"2009 Fifth International Conference on Natural Computation","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125262099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Optimization for the Bioconversion of Succinic Acid Based on Response Surface Methodology and Back-Propagation Artificial Neural Network 基于响应面法和反向传播人工神经网络的丁二酸生物转化优化
2009 Fifth International Conference on Natural Computation Pub Date : 2009-08-14 DOI: 10.1109/ICNC.2009.20
Xingjiang Li, Shaotong Jiang, L. Pan, Zhaojun Wei
{"title":"Optimization for the Bioconversion of Succinic Acid Based on Response Surface Methodology and Back-Propagation Artificial Neural Network","authors":"Xingjiang Li, Shaotong Jiang, L. Pan, Zhaojun Wei","doi":"10.1109/ICNC.2009.20","DOIUrl":"https://doi.org/10.1109/ICNC.2009.20","url":null,"abstract":"At the base of primary culture medium, single factor experiment showed that CO2 and H2 and VH were distinct factors. The response surface methodology was employed to evaluate the interaction of those factors, and the result showed that there was obvious interaction between those factors, and that 74.60 g/L succinic acid was gained when the condition was as following: 66 % CO2 and 4.9% H2 and 5.9 mmol/L VH. Then a three-layer Back-Propagation artificial neural network was employed for the simulating and predicting, and the result showed that 78.10 g/L succinic acid was gained when the condition was as following: 67% CO2 and 4.8% H2 and 5.9 mmol/L VH. Comparison with the regressive analysis of the response surface methodology, the artificial neural network had better ability of predicting, since its predicting error was 0.17% while that of response surface methodology was 0.81%.","PeriodicalId":235382,"journal":{"name":"2009 Fifth International Conference on Natural Computation","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125423346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
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