{"title":"The Effect of Camera Calibration Space on Visual Pose's Precision","authors":"Jing Zhou, Yingming Hao, F. Zhu, Lei He","doi":"10.1109/ICNC.2007.720","DOIUrl":"https://doi.org/10.1109/ICNC.2007.720","url":null,"abstract":"In this paper, the relationship between the camera calibration space and measurement error is analyzed in order to enhance the precision of a model based monocular vision pose estimation system. We proved that the calibration error of camera intrinsic parameters can be reduced when the calibration space is designed in a full field of view no matter how small the imaging range of the measuring area is, thus obtaining better precision of pose estimation. This conclusion provides important guidance for engineering application of the visual pose measurement system.","PeriodicalId":250881,"journal":{"name":"Third International Conference on Natural Computation (ICNC 2007)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121266123","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":"Adaptive Selection of Wavelet Basis Based on Genetic Algorithm and Its Application","authors":"Zhonghui Luo, Leping Liu","doi":"10.1109/ICNC.2007.162","DOIUrl":"https://doi.org/10.1109/ICNC.2007.162","url":null,"abstract":"An adaptive selection of wavelet basis is presented in this paper. Based on the constructive theory of orthogonal binary wavelet basis, a parameter expression equation of orthogonal wavelet basis is constructed and a adaptive goal function of de-noised effect is defined. By applying genetic optimization method, the best wavelet basis was obtained, and the correlative arithmetic is presented. Applying the optimal wavelet basis to eliminate noises from signals, and computed the correlation dimension of the de-noised signals as fault feature. Simulation and experiments show that the adaptive wavelet de-noising makes the mechanical fault feature extraction more reliable.","PeriodicalId":250881,"journal":{"name":"Third International Conference on Natural Computation (ICNC 2007)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127178529","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":"Active Service in Migrating Workflow System","authors":"Rui Wang, Guangzhou Zeng","doi":"10.1109/ICNC.2007.158","DOIUrl":"https://doi.org/10.1109/ICNC.2007.158","url":null,"abstract":"This paper describes the architecture of active service model of migrating workflow system. Virtualization technologies are available for all the resources needed to construct virtual services specific group. The architecture is designed to support organizations coevolutionary for providing workflow service. In particular, these technologies enable the creation of dynamic pools of virtual resources that can be aggregated on-demand for workflow specific goal. This paper reviews the introduction and motivation for active service approach, describes the architecture of migrating workflow system, discusses the technologies used in active service , which represents steps towards the end goal of building virtual service group and organization coevolutionary algorithm, then compares this proposition with related works.","PeriodicalId":250881,"journal":{"name":"Third International Conference on Natural Computation (ICNC 2007)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127491029","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":"A Multi-population Particle Swarm Optimizer and its Application to Blind Multichannel Estimation","authors":"Ying Gao, Zhaohui Li, Xiao Hu, Huailiang Liu","doi":"10.1109/ICNC.2007.72","DOIUrl":"https://doi.org/10.1109/ICNC.2007.72","url":null,"abstract":"In this paper, a multi-population particle swarm optimizer based on Lotka-Volterra competition equation is first proposed. The cooperative coevolution in the field of is involved into original particle swarm optimizer, and populations size is adjusted adaptively based on multi- population Lotka-Volterra competition equation. Then, the algorithm is applied to blind multichannel estimation by optimizing an error function for the outputs of a multichannel system. The experiment results demonstrate that the proposed algorithm is superior to original particle swarm optimization algorithm, and is effective to blind multichannel estimation.","PeriodicalId":250881,"journal":{"name":"Third International Conference on Natural Computation (ICNC 2007)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124841561","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":"SVM-based Fingerprint Classification Using Orientation Field","authors":"Luping Ji, Zhang Yi","doi":"10.1109/ICNC.2007.700","DOIUrl":"https://doi.org/10.1109/ICNC.2007.700","url":null,"abstract":"This paper presents a classification method of fingerprint using orientation field and support vector machines. It estimates orientation field through pixel gradient, then calculates the percentages of the directional block classes. These percentages are combined as a four dimensional vector, by which the trained hierarchical classifier classifies the fingerprint into one of the six classes it belongs to. Experiments show that this method has high classification accuracy as well as low computational time cost.","PeriodicalId":250881,"journal":{"name":"Third International Conference on Natural Computation (ICNC 2007)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124910538","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":"Predicting Total Hydro Carbons Amount of Air Using Artificial Neural Network","authors":"S. Sargolzaei, K. Faez, A. Sargolzaei","doi":"10.1109/ICNC.2007.560","DOIUrl":"https://doi.org/10.1109/ICNC.2007.560","url":null,"abstract":"In this article, parameters affecting on formation and elimination of hydrocarbons using artificial neural network are considered and a model to predict THC (total hydrocarbon) amount in air using neural network is earned. Also using neural network model and surveying effect of each parameters on THC amount, optimization of offered model is done. The database to get mentioned model consists 1500 samples of current information in two stations of quality control of Tehran city air. Results of using artificial neural network in prediction of THC amount indicate that neural network model is suitable for predicting THC amount. Also to compare improvement of implementing THC prediction model using artificial neural network, a multivariable regression model is used to predict THC amount and its results indicate that MSE is very low when we use artificial neural network.","PeriodicalId":250881,"journal":{"name":"Third International Conference on Natural Computation (ICNC 2007)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124983424","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":"Continuous ant colony optimization algorithms in a support vector regression based financial forecasting model","authors":"Wei‐Chiang Hong, Yu-Fen Chen, Peng Chen, Yi-Hsuan Yeh","doi":"10.1109/ICNC.2007.315","DOIUrl":"https://doi.org/10.1109/ICNC.2007.315","url":null,"abstract":"Traditional time series forecasting models are difficult to capture the nonlinear patterns. Support vector regression (SVR) has been successfully used to solve nonlinear regression and times series problems. However, parameters determination for a SVR model is competent to the forecasting accuracy. Several evolutionary algorithms, such as genetic algorithms and simulated annealing algorithms have been used to the parameters selection, however, these algorithms often suffer the problem of being trapped in local optimum. This investigation used continuous ant colony optimization algorithms in a SVR model for selecting suitable parameters, in which encouraging local search in areas where forecasting accuracy improvement continues to be made, then, autocatalytically converge to promising regions. Numerical examples of exchange rates forecasting from an existing literature are employed to compare the performance of the proposed model. Experiment results show that the proposed model outperforms the other approaches in the literature.","PeriodicalId":250881,"journal":{"name":"Third International Conference on Natural Computation (ICNC 2007)","volume":"92 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125973919","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":"Robust Position Tracking for Mobile Robots with Adaptive Evolutionary Particle Filter","authors":"Zhuohua Duan, Zixing Cai, Jinxia Yu","doi":"10.1109/ICNC.2007.641","DOIUrl":"https://doi.org/10.1109/ICNC.2007.641","url":null,"abstract":"Robust position tracking is a challengeable issue for mobile robot in presence of faults. In the paper, an adaptive evolutionary particle filter is designed to achieve robust position tracking for wheeled mobile robot when the robot is subjected to faults such as sensor faults and wheel slippage. Firstly, the kinematics models of wheeled mobile robots and the measurement models of laser range finder are derived, five kinds of residual features are extracted and faults are detected according residual features. Secondly, an adaptive evolutionary particle filter is designed for robust localization, which includes two key steps: (1) adapting the proposal distribution according to residual features, (2) evolutionary operators, which are tuned with unnormalized weights of particles, are designed to recover the diversity of particle sets. Lastly, the presented method is testified in a real mobile robot.","PeriodicalId":250881,"journal":{"name":"Third International Conference on Natural Computation (ICNC 2007)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126115652","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":"Application of the Improved Genetic Algorithms With Real Code on GPS Data Processing","authors":"Zhimin Liu, Zhixing Du, Rong Zou","doi":"10.1109/ICNC.2007.264","DOIUrl":"https://doi.org/10.1109/ICNC.2007.264","url":null,"abstract":"Because of some advantages, such as simpleness, parallel and robustness on resolving numerical value optimization problems, genetic algorithms (GA) were improved and applied on global positioning system (GPS) high precision positioning data processing. Aimed on the integer nature of double difference ambiguities and the real nature of baseline coordinates, the real-coded methods of GA were improved in order to satisfy to the solution sets characteristic of GPS positioning. And then the corresponding genetic operators and control parameters were modified. The method to solve synchronously the GPS relative positioning was raised based on nonlinear least-square principle. So the dependence on the accuracy of float solution was avoided, and the improved GA helped to enhance the search optimum success rate. Through a large number of cases, the tests of the proposed method were practiced and it was verified that this improved GA were superior to data processing of GPS carrier phase relative positioning resolution on stability and efficiency.","PeriodicalId":250881,"journal":{"name":"Third International Conference on Natural Computation (ICNC 2007)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125317614","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":"A Cell Transmission Model and Its Application in Optimizing the Location of Variable Message Signs","authors":"Huayan Shang, Haijun Huang","doi":"10.1109/ICNC.2007.7","DOIUrl":"https://doi.org/10.1109/ICNC.2007.7","url":null,"abstract":"The variable message signs (VMS) have been widely used in guiding and managing the dynamic traffic with development of intelligent transportation technologies. This paper employs a cell transmission model to study the location problem of VMS information board. Simulation results show that an optimal VMS location exists in deed for minimizing the total travel time of the traffic system. Route choice probabilities adopted before and after a traffic incident significantly affect the optimal VMS location. It is found that the VMS should be placed far from the incident site if the incident makes traffic be held up for long time.","PeriodicalId":250881,"journal":{"name":"Third International Conference on Natural Computation (ICNC 2007)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116519163","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}