International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications最新文献
Shi Yu, Liang Weidong, Xue Cheng, Fan Ding, Chen Jianhong
{"title":"Intelligent neural network control system for gas metal arc welding","authors":"Shi Yu, Liang Weidong, Xue Cheng, Fan Ding, Chen Jianhong","doi":"10.1109/ICNC.2010.5583868","DOIUrl":"https://doi.org/10.1109/ICNC.2010.5583868","url":null,"abstract":"A neural network control system for keeping arc stability and decreasing the spatter during gas metal arc welding have been created. The characterization and relationship between arc sound and arc stability was studied. Tree kinds of neural network control constructions were presented. After simulated the static and dynamic performance in welding processes, it can be found that the error back propagating model neural network have better properties. The factors affecting the simulating results and the dynamic response quality have also been analyzed.","PeriodicalId":87274,"journal":{"name":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","volume":"4 1","pages":"1376-1379"},"PeriodicalIF":0.0,"publicationDate":"2010-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78953927","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}
{"title":"Superplasticity prediction and application of albronze based on artificial neural network","authors":"Guo Junqing, Chen Fuxiao, Yang Yongshun, Li Hejun","doi":"10.1109/ICNC.2010.5583350","DOIUrl":"https://doi.org/10.1109/ICNC.2010.5583350","url":null,"abstract":"The superplastic performances prediction of albronze based on artificial neural network was studied in this paper. Used Levenberg-Marquardt algorithm, the predication model of BP neural network which reflects the relationship between the superplastic performances and tension conditions was founded. The superplasticity and optimized condition of albronze were forecasted and the superplastic extrusion tests of solid cage was produced also. The results showed that the error of tests data and prediction was less than 8.5%. It was indicated that the prediction of albronze superplasticity used artificial neural network was effective and feasible.","PeriodicalId":87274,"journal":{"name":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","volume":"24 1","pages":"668-670"},"PeriodicalIF":0.0,"publicationDate":"2010-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91378858","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}
{"title":"Long memory macroeconomic model of the term structure of interest rates","authors":"Z. Yi, Feng Jiang","doi":"10.1109/ICNC.2010.5583966","DOIUrl":"https://doi.org/10.1109/ICNC.2010.5583966","url":null,"abstract":"In this paper, we employ the Sowell (1989) multivariate long memory model to describe the dynamic behaviors of our macro system. Moreover, we incorporate the partial seasonal adjustment operator into our macro model by which we significantly reduce the AR lag order lower to one,hence reducing a large amount of parameters. Empirically, we apply the estimation procedure of Hualde and Robinson (2006). We found that 3 month short interest rate is fractionally cointegrated with the long term yield, implying a stable long run relationship between them.","PeriodicalId":87274,"journal":{"name":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","volume":"47 1","pages":"2975-2979"},"PeriodicalIF":0.0,"publicationDate":"2010-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72833509","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}
{"title":"Optimization for Giant magnetostrictive smart component based on multi-objective genetic algorithm","authors":"X. Sui, Zhang-Rong Zhao, Xu-Ming Wang, Xia-Jun Meng","doi":"10.1109/ICNC.2010.5583153","DOIUrl":"https://doi.org/10.1109/ICNC.2010.5583153","url":null,"abstract":"In order to machine the non-cylinder piston pinhole, a new method is proposed by applying the Giant magnetostrictive materials (GMM) component. An optimization design model combining the smart component genetic algorithm with the finite element method for GMM smart component is established. Nondominated sorting genetic algorithm (NSGA) is used to optimize the model. The optimum results show that the NSGA combining with finite element method is a good way to carry out the optimization design of GMM smart component.","PeriodicalId":87274,"journal":{"name":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","volume":"75 1","pages":"466-470"},"PeriodicalIF":0.0,"publicationDate":"2010-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86402764","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}
{"title":"Optimization method for the layout of IMUs in deformation detection system of warship based on genetic algorithm","authors":"Liu Aili, Ma Hongxu","doi":"10.1109/ICNC.2010.5584820","DOIUrl":"https://doi.org/10.1109/ICNC.2010.5584820","url":null,"abstract":"The deformation of warship will influence the accuracy of angular position about the equipment in the deck. IMUs(Inertial Measurement Unit, laser gyros and accelerometers) are installed on various points of the warship to estimate the deformations. Genetic algorithm is utilized for the optimization of the layout of the IMUs, the fitness function of the genetic algorithm is built by the ship's Modal Assurance Criterion (MAC) matrix. Results show that the Genetic algorithm based method presented in this paper can give an optimal layout of the IMUs for detecting the deformation of the warship.","PeriodicalId":87274,"journal":{"name":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","volume":"85 1","pages":"4014-4017"},"PeriodicalIF":0.0,"publicationDate":"2010-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82068347","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}
{"title":"Optimization of preventive maintenance period based on hybrid swarm intelligence","authors":"Sa-sa Ma","doi":"10.1109/ICNC.2010.5582956","DOIUrl":"https://doi.org/10.1109/ICNC.2010.5582956","url":null,"abstract":"It was analyzed that there were some problems such as parameters value settings etc when the ant colony optimization (ACO) was applied in the PM period optimization process. And it was put forward that the particle swarm optimization (PSO) was brought into the ACO algorithm to form a new hybrid swarm optimization: Particle Swarm and Ant Colony Optimization (PS_ACO). This new hybrid algorithm can modify the optimization rules and geographic division of ACO, and can partly solve some problems about the worse precision and inefficient optimization coming from unsuitable parameters values setting of ACO and random PM period solution. This PS_ACO algorithm was applied in the optimization process of series-parallel system PM period. The experimental data shows that: the PS_ACO can partly improve the optimization efficiency and precision, and relatively weaken the influence of parameters value settings to the optimization result.","PeriodicalId":87274,"journal":{"name":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","volume":"38 1","pages":"2656-2659"},"PeriodicalIF":0.0,"publicationDate":"2010-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85728738","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}
{"title":"An amelioration Particle Swarm Optimization algorithm","authors":"Huayong, Ming-qing, Hang","doi":"10.1109/ICNC.2010.5583201","DOIUrl":"https://doi.org/10.1109/ICNC.2010.5583201","url":null,"abstract":"a new amelioration Particle Swarm Optimization (SARPSO) based on simulated annealing (SA), asynchronously changed learning genes (ACLG) and roulette strategy was proposed because the classical Particle Swarm Optimization (PSO) algorithm was easily plunged into local minimums. SA had the ability of probability mutation in the search process, by which the search processes of PSO plunging into local minimums could be effectively avoided; ACLG could improve the ability of global search at the beginning, and it was propitious to be convergent to global optimization in the end; the roulette strategy could avoid prematurity of the algorithm. The emulation experiment results of three multi-peaking testing functions had shown the validity and practicability of the SARPSO algorithm.","PeriodicalId":87274,"journal":{"name":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","volume":"64 1","pages":"2571-2575"},"PeriodicalIF":0.0,"publicationDate":"2010-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80192623","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}
{"title":"The research of building production-oriented data mart for mine enterprises based on data mining","authors":"Xinrui Liu, Hong-Bin Ma, Hongdi Zhao, F. Ren","doi":"10.1109/ICNC.2010.5583990","DOIUrl":"https://doi.org/10.1109/ICNC.2010.5583990","url":null,"abstract":"According to the demands of digital mine and smart mine, taking account of present status of mine information process, based on deep-going analysis of characteristics of mining technology, we study how to mine and discovery knowledge from immense mine data. Aim at building green and intelligent mine, we mainly discuss the methods and architectures of establishing production-oriented mine data mart with data mining concepts and techniques, which is not only to satisfy the needs of diary production but decision-making analysis as well.","PeriodicalId":87274,"journal":{"name":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","volume":"136 1","pages":"2186-2189"},"PeriodicalIF":0.0,"publicationDate":"2010-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76739077","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}
{"title":"Parameters identification of coupled seepage and stress field based on genetic algorithms","authors":"Xianghui Deng, Rui Wang","doi":"10.1109/ICNC.2010.5583713","DOIUrl":"https://doi.org/10.1109/ICNC.2010.5583713","url":null,"abstract":"For rock mechanics and civil engineering, how to obtain the parameters in seepage field and stress field is very complicated and key for analyzing the coupling problem of seepage field and stress field. Therefore, aim of this paper is to study the parameter inversion method with which the parameters of two fields can be obtained. On the basis of the hydraulic heads and displacements measured, combining with genetic algorithm, the parameter inversion method of coupled seepage and stress field is putting forward. Considering the condition of drawdown of reservoir water level, according to results of coupled seepage and stress analysis assumed to be the measured data, the parameter inversion analysis was made. The results show that the method and calculation program of inverse analysis are valid and feasible in this engineering example.","PeriodicalId":87274,"journal":{"name":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","volume":"85 1","pages":"4171-4175"},"PeriodicalIF":0.0,"publicationDate":"2010-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76927176","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}
{"title":"Fault diagnosis of engine mission using modified Elman neural network","authors":"Yu guo Wu, C. Song, Li Ping Shi","doi":"10.1109/ICNC.2010.5582900","DOIUrl":"https://doi.org/10.1109/ICNC.2010.5582900","url":null,"abstract":"Based on the fault diagnosis system of engine mission and Elman neural network, it analyses the shortage diagnosis of Elman network, and puts forward the modified Elman network, and applied in fault diagnosis of engine mission. By using conventional “frequency domain” analysis method, modified Elman networks fault diagnosis of engine mission is carried out. It is proved that fault diagnosis of engine mission based on neural networks has upper precision and diagnosed engine mission, improved effectiveness and quality of diagnosis.","PeriodicalId":87274,"journal":{"name":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","volume":"30 1","pages":"996-998"},"PeriodicalIF":0.0,"publicationDate":"2010-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88220032","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}