With the development of network technology, E-Learning, becomes more popular, most learners want to get a right answer quickly. in order, to meet the need of learners, in this paper, firstly we construct a simple index structure based on the contents of chapters and sections according to the characteristic oft E-learning, secondly, we propose a group of quick location algorithms according to the index structure, including Simple vector distance classification algorithm, Bayesian algorithm, KNN¿K nearest neighbor¿algorithm etc, Test results show that the algorithm can reduce the searching time about 50%, thus remarkably increase the match speed of problem and answer.
{"title":"Research and Implementation of Fast Locating Algorithm in Intelligent QA System","authors":"Ming Zhao","doi":"10.1109/WGEC.2009.30","DOIUrl":"https://doi.org/10.1109/WGEC.2009.30","url":null,"abstract":"With the development of network technology, E-Learning, becomes more popular, most learners want to get a right answer quickly. in order, to meet the need of learners, in this paper, firstly we construct a simple index structure based on the contents of chapters and sections according to the characteristic oft E-learning, secondly, we propose a group of quick location algorithms according to the index structure, including Simple vector distance classification algorithm, Bayesian algorithm, KNN¿K nearest neighbor¿algorithm etc, Test results show that the algorithm can reduce the searching time about 50%, thus remarkably increase the match speed of problem and answer.","PeriodicalId":277950,"journal":{"name":"2009 Third International Conference on Genetic and Evolutionary Computing","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115787246","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}
In order to realize the text classification and spam filtering, the Naive Bayesian algorithm estimate what class are the text in by basing on some statistical probability values in accordance with the characteristic in straining sample, but it is easy to expose the overflow problem, this article will optimize the algorithm by setting the threshold, the optimization strategy is comparing the times that the probability of each class exceed the threshold and the accumulated probability values at the same times. Compare with the existing method, experimental result show the new method not only can solve the overflow problem, but also improve the classification effect effectively.
{"title":"The Optimization of Threshold-Based Naive Bayesian Algorithm","authors":"Xin Wang, Hua Jiang","doi":"10.1109/WGEC.2009.161","DOIUrl":"https://doi.org/10.1109/WGEC.2009.161","url":null,"abstract":"In order to realize the text classification and spam filtering, the Naive Bayesian algorithm estimate what class are the text in by basing on some statistical probability values in accordance with the characteristic in straining sample, but it is easy to expose the overflow problem, this article will optimize the algorithm by setting the threshold, the optimization strategy is comparing the times that the probability of each class exceed the threshold and the accumulated probability values at the same times. Compare with the existing method, experimental result show the new method not only can solve the overflow problem, but also improve the classification effect effectively.","PeriodicalId":277950,"journal":{"name":"2009 Third International Conference on Genetic and Evolutionary Computing","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130780990","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}
As a complex system boiler combustion process has the characteristics--high non-linearity, strong jamming, strong coupling and large lagging, meanwhile its internal and external disturbance are very frequent, and fuel quantity can not be exactly measured, so using conventional control scheme is hard to solve the boiler combustion control problem with non-linearity and long time lags. Improved Dynamic Programming is the method of interacting with the system (environment) and improving control effect. This method mainly consisting of three modules: model, critic and action. This paper uses dual-heuristic dynamic programming to consider the solution of boiler combustion multivariable control system, realize the emulated control of boiler combustion process, and analyze learning capacity, controlling effect and adaptive capability of the approach. Finally all of three states reach the expected control objectives.
{"title":"Improved Dynamic Programming Based on BPNN for Combustion Control of Boiler","authors":"Baosheng Yang, Xiaoying Yang","doi":"10.1109/WGEC.2009.93","DOIUrl":"https://doi.org/10.1109/WGEC.2009.93","url":null,"abstract":"As a complex system boiler combustion process has the characteristics--high non-linearity, strong jamming, strong coupling and large lagging, meanwhile its internal and external disturbance are very frequent, and fuel quantity can not be exactly measured, so using conventional control scheme is hard to solve the boiler combustion control problem with non-linearity and long time lags. Improved Dynamic Programming is the method of interacting with the system (environment) and improving control effect. This method mainly consisting of three modules: model, critic and action. This paper uses dual-heuristic dynamic programming to consider the solution of boiler combustion multivariable control system, realize the emulated control of boiler combustion process, and analyze learning capacity, controlling effect and adaptive capability of the approach. Finally all of three states reach the expected control objectives.","PeriodicalId":277950,"journal":{"name":"2009 Third International Conference on Genetic and Evolutionary Computing","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131155077","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}
Coal-fired boiler operation is confronted with two requirements to reduce its operation cost and to lower its emission. In this paper, a model for boiler efficiency and a model for NOx emission are set up respectively by RBF neural network. In order to obtain more accurate models without trying repeatedly, GA is introduced to optimize the parameter of RBF network. Then Non-Dominated Sorting Genetic Algoritthm-II is employed to perform a search to determine the optimum solution of boiler operation after we obtain boiler combustion model. Experimental results prove that the method proposed in this paper can improve boiler efficiency and reduce NOx emission obviously. Through analysis, we can see this method is better than the traditional method which uses weights to combine boiler efficiency and NOx emission in one objective function.
{"title":"Combustion Optimization Based on RBF Neural Network and Multi-objective Genetic Algorithms","authors":"Dongfeng Wang, Q. Li, Li Meng, P. Han","doi":"10.1109/WGEC.2009.47","DOIUrl":"https://doi.org/10.1109/WGEC.2009.47","url":null,"abstract":"Coal-fired boiler operation is confronted with two requirements to reduce its operation cost and to lower its emission. In this paper, a model for boiler efficiency and a model for NOx emission are set up respectively by RBF neural network. In order to obtain more accurate models without trying repeatedly, GA is introduced to optimize the parameter of RBF network. Then Non-Dominated Sorting Genetic Algoritthm-II is employed to perform a search to determine the optimum solution of boiler operation after we obtain boiler combustion model. Experimental results prove that the method proposed in this paper can improve boiler efficiency and reduce NOx emission obviously. Through analysis, we can see this method is better than the traditional method which uses weights to combine boiler efficiency and NOx emission in one objective function.","PeriodicalId":277950,"journal":{"name":"2009 Third International Conference on Genetic and Evolutionary Computing","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123758458","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}
Considering the character of bus passenger travel, a bus travel transit path query algorithm with the least transfer times was brought out, which was based on ant algorithm and Dijkstra algorithm of bus stops query. Using the path selection character of ant looking for food and the principle of refreshing bus-line’s hormone intensity, the algorithm achieved the optimization goals of bus travel path selection, which were the least transfer times and bus stops. Application results show that this method can reflect the real situation.
{"title":"Bus Travel Transit Path Query Algorithm Based on Ant Algorithm","authors":"Wen-yong Li, Xue-wu Chen, Bo Yang","doi":"10.1109/WGEC.2009.13","DOIUrl":"https://doi.org/10.1109/WGEC.2009.13","url":null,"abstract":"Considering the character of bus passenger travel, a bus travel transit path query algorithm with the least transfer times was brought out, which was based on ant algorithm and Dijkstra algorithm of bus stops query. Using the path selection character of ant looking for food and the principle of refreshing bus-line’s hormone intensity, the algorithm achieved the optimization goals of bus travel path selection, which were the least transfer times and bus stops. Application results show that this method can reflect the real situation.","PeriodicalId":277950,"journal":{"name":"2009 Third International Conference on Genetic and Evolutionary Computing","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124035613","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}
The ship hydrodynamic pressure signal is generally hard to detect from the rough ocean wave hydrodynamic pressure background signal. An algorithm based on neural network prediction is provided to detect the ship pressure signal from the ocean wave pressure signal. The predictions of hydrodynamic pressure signal are compared with measurements of the same variables to form prediction errors that are used to test for the presence of the ship pressure signal. If the prediction errors are relatively high, it will mean the appearance of a ship hydrodynamic pressure signal. Through the simulation results on the simulated and the measurement data, the algorithm based on feed forward neural network prediction proved its validity.
{"title":"Ship Hydrodynamic Pressure Signal Detection Based on Neural Network Prediction","authors":"Xiaobing Zhang, Yizhuo Jia","doi":"10.1109/WGEC.2009.173","DOIUrl":"https://doi.org/10.1109/WGEC.2009.173","url":null,"abstract":"The ship hydrodynamic pressure signal is generally hard to detect from the rough ocean wave hydrodynamic pressure background signal. An algorithm based on neural network prediction is provided to detect the ship pressure signal from the ocean wave pressure signal. The predictions of hydrodynamic pressure signal are compared with measurements of the same variables to form prediction errors that are used to test for the presence of the ship pressure signal. If the prediction errors are relatively high, it will mean the appearance of a ship hydrodynamic pressure signal. Through the simulation results on the simulated and the measurement data, the algorithm based on feed forward neural network prediction proved its validity.","PeriodicalId":277950,"journal":{"name":"2009 Third International Conference on Genetic and Evolutionary Computing","volume":"303 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124284429","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}
Xiaowei Han, H. Cao, Zhonghu Yuan, Hongying Zhao, Lei Yan
Based on the characteristics of color space transform between RGB and HSI, an algorithm of color difference measurement for color image is presented. The degree of scatter about color space distribution of a given image region is determined by computing the sum of color difference between every pixel and the other pixels of the image region. Then an effective feature template, which is then used in color image matching, is chosen according to the degree value. Furthermore, template matching is applied to obtain relative displacement between two images to mosaicked. A function of brightness transform is built by Least Mean Square (LMS). According to the function built, brightness of each pixel in one color image is adjusted when necessary, and then the brightness difference between two images can be eliminated. Experimental results show that the proposed approach has good precision of image mosaicking and capacity of anti-jamming for brightness.
{"title":"An Approach of Color Image Mosaicking Based on Color Vision Characteristics","authors":"Xiaowei Han, H. Cao, Zhonghu Yuan, Hongying Zhao, Lei Yan","doi":"10.1109/WGEC.2009.133","DOIUrl":"https://doi.org/10.1109/WGEC.2009.133","url":null,"abstract":"Based on the characteristics of color space transform between RGB and HSI, an algorithm of color difference measurement for color image is presented. The degree of scatter about color space distribution of a given image region is determined by computing the sum of color difference between every pixel and the other pixels of the image region. Then an effective feature template, which is then used in color image matching, is chosen according to the degree value. Furthermore, template matching is applied to obtain relative displacement between two images to mosaicked. A function of brightness transform is built by Least Mean Square (LMS). According to the function built, brightness of each pixel in one color image is adjusted when necessary, and then the brightness difference between two images can be eliminated. Experimental results show that the proposed approach has good precision of image mosaicking and capacity of anti-jamming for brightness.","PeriodicalId":277950,"journal":{"name":"2009 Third International Conference on Genetic and Evolutionary Computing","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117170332","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}
This paper applied the Methods which based on GEP in compress multi-streams. The contributions of this paper include: 1) giving an introduction to data function finding based on GEP(DFF-GEP), defining the main conception of Multi-Streams, and revealing the map relation in it; 2) putting forward the Compression Algorithm for Multi-Streams according to map relation lied in data between data streams; and 3)providing an experience with the real data and find that (3.1) the compression ratio of the new methods is 120¿150 times as the traditional wavelets method, and 35¿70 times as the wavelets and coincidence method; (3.2) the relative error of the new method is about 3¿, yet maximum relative error is 0.01 by using the traditional relative error standard, the precision is improved from 7% to 15% as compared with the traditional method.
{"title":"A Compression Algorithm for Multi-streams Based on GEP","authors":"Chao Ding, Chang-an Yuan, Xiao Qin, Yu-zhong Peng","doi":"10.1109/WGEC.2009.26","DOIUrl":"https://doi.org/10.1109/WGEC.2009.26","url":null,"abstract":"This paper applied the Methods which based on GEP in compress multi-streams. The contributions of this paper include: 1) giving an introduction to data function finding based on GEP(DFF-GEP), defining the main conception of Multi-Streams, and revealing the map relation in it; 2) putting forward the Compression Algorithm for Multi-Streams according to map relation lied in data between data streams; and 3)providing an experience with the real data and find that (3.1) the compression ratio of the new methods is 120¿150 times as the traditional wavelets method, and 35¿70 times as the wavelets and coincidence method; (3.2) the relative error of the new method is about 3¿, yet maximum relative error is 0.01 by using the traditional relative error standard, the precision is improved from 7% to 15% as compared with the traditional method.","PeriodicalId":277950,"journal":{"name":"2009 Third International Conference on Genetic and Evolutionary Computing","volume":"157 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123099348","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}
Epidemic contagion dynamic model can better reflect the dynamics of crisis in the enterprise group. Based on computer simulation method, studied the enterprise risk management mechanism and given the countermeasure.
{"title":"Study on Mechanism of Enterprise Group' Crisis Management Based on the Epidemic Contagion Dynamic Model","authors":"Ji Guo, Xianhua Wu, Yi Yang","doi":"10.1109/WGEC.2009.187","DOIUrl":"https://doi.org/10.1109/WGEC.2009.187","url":null,"abstract":"Epidemic contagion dynamic model can better reflect the dynamics of crisis in the enterprise group. Based on computer simulation method, studied the enterprise risk management mechanism and given the countermeasure.","PeriodicalId":277950,"journal":{"name":"2009 Third International Conference on Genetic and Evolutionary Computing","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122791735","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}
We study the circular packing problem (CPP) which consists of packing a set of circles of known radii into a larger containing circle without overlapping. The objective is to determine the smallest radius of the containing circle and the coordinates of the center of every packed circle. To solve CPP, we propose a heuristic simulated annealing (HSA) algorithm that incorporates heuristic neighborhood search mechanism and the gradient descent method into the simulated annealing procedure. The special neighborhood search mechanism can avoid the disadvantage of blind search in the simulated annealing algorithm and the gradient descent method can speed up searching the global optimal configuration. The computational results, on a set of instances taken from the literature, show the effectiveness of the proposed algorithm.
{"title":"A Heuristic Simulated Annealing Algorithm for the Circular Packing Problem","authors":"Jingfa Liu, Yu Zheng, Wenjie Liu","doi":"10.1109/WGEC.2009.170","DOIUrl":"https://doi.org/10.1109/WGEC.2009.170","url":null,"abstract":"We study the circular packing problem (CPP) which consists of packing a set of circles of known radii into a larger containing circle without overlapping. The objective is to determine the smallest radius of the containing circle and the coordinates of the center of every packed circle. To solve CPP, we propose a heuristic simulated annealing (HSA) algorithm that incorporates heuristic neighborhood search mechanism and the gradient descent method into the simulated annealing procedure. The special neighborhood search mechanism can avoid the disadvantage of blind search in the simulated annealing algorithm and the gradient descent method can speed up searching the global optimal configuration. The computational results, on a set of instances taken from the literature, show the effectiveness of the proposed algorithm.","PeriodicalId":277950,"journal":{"name":"2009 Third International Conference on Genetic and Evolutionary Computing","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124943972","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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