{"title":"Research on Forecast of Sugar Price Based on Improved Neural Network","authors":"Yongchun Xu, Shiquan Shen, Zhen Chen","doi":"10.1109/IITSI.2009.9","DOIUrl":"https://doi.org/10.1109/IITSI.2009.9","url":null,"abstract":"According to the feature of market fluctuations in the price of sugar, an optimization algorithm based on improved genetic neural network training was proposed in this paper. A population optimization model on adaptive crossover and mutation operator and niche was designed, by applying gray theory and technology, the sugar price data was processed. A multi-dimensional learning sample and teacher sample for improved genetic neural network training was constructed. Finally, the trend of sugar prices of 1-2 weeks in year 2008 to 2009 was predicted by cases, the comparison of the forecast algorithm versus gray linear systems, S-BP, SGA-BP algorithm showed the integrated optimization of forecast accuracy and forecast effect.","PeriodicalId":308774,"journal":{"name":"2009 Second International Symposium on Intelligent Information Technology and Security Informatics","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117175608","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":"Research on Electric Power Steering System Based on Compound Control of CMAC and PID","authors":"Peilin Shi, Shi-zhan Gao, Yi Wang","doi":"10.1109/IITSI.2009.15","DOIUrl":"https://doi.org/10.1109/IITSI.2009.15","url":null,"abstract":"Because of the complex nonlinearity of electric power steering system, the actual current of motor can’t follow the tracks of the target current well with PID controller. A compound controller of CMAC and PID is proposed for it. This controller realized the feedback control with traditional PID controller to make the electric power steering system stable, and realized the feed forward control with CMAC neural network controller to increase the response speed and control precision. Simulation results showed that actual current of motor can follow the tracks of the target current very well with the compound controller. Moreover, the compound control system of CMAC and PID is less sensitive to the change of parameters than that in PID control system.","PeriodicalId":308774,"journal":{"name":"2009 Second International Symposium on Intelligent Information Technology and Security Informatics","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117285862","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":"Mixed Gases Recognition Based on Feedforward Neural Network","authors":"Zhou Tao, Wang Lei","doi":"10.1109/IITSI.2009.35","DOIUrl":"https://doi.org/10.1109/IITSI.2009.35","url":null,"abstract":"The three gas sensors array was developed in this paper, and it was encapsulated through the Micro-Electro-Mechanical Systems (MEMS) technique. The gas sensors applied the heating unit to improve the sensitivity. The gas sensor which was sensitive to the special gas could be selected in the different application fields. The sampling experiments showed that the gas sensors have the higher sensitivity and better repeatability and cross sensitivity. Moreover, the pattern recognition algorithms based on a feedforward neural network were studied in the paper. They have the higher pattern recognition capacity, the convergence rate and simpler training method. The intelligent recognition system which adopted the gas sensor array and feedforward neural network was design. The recognition experiments showed the system has better identification effect and higher accuracy.","PeriodicalId":308774,"journal":{"name":"2009 Second International Symposium on Intelligent Information Technology and Security Informatics","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124835987","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":"Computer Simulation of Temperature Characteristics in the Process of Vacuum and Selective FIR Drying for Litchi","authors":"F. Xu, Changyou Li, Zhen Chen","doi":"10.1109/IITSI.2009.14","DOIUrl":"https://doi.org/10.1109/IITSI.2009.14","url":null,"abstract":"Based on the spherical character of litchi, a heat and mass transfer model on shell-membrane and flesh-stone drying for litchi under the liquid-vapor interface moving was established and the temperature equation under shrinkage with interface moving was numerically solved. In 2 drying methods of continuous heating and tempering-intermittent heating involving 3 irradiance of 600, 800, 1200W/m2, temperature of drying medium 330K and vacuum degree -0.09Mpa, the temperature of flesh was numerically simulated by using VB6.0 program and made a comparative. Thus the simulation results could be used to provide means of precise regulation on transformation of critical temperature for vacuum and selective FIR litchi drying.","PeriodicalId":308774,"journal":{"name":"2009 Second International Symposium on Intelligent Information Technology and Security Informatics","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125889260","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}
Guowei Tang, X. Zhong, Fangzhou Zhang, Zhen-Ni Jin
{"title":"X-Ray Image Edge Detection Based on Wavelet Transform and Lipschitz Exponent","authors":"Guowei Tang, X. Zhong, Fangzhou Zhang, Zhen-Ni Jin","doi":"10.1109/IITSI.2009.50","DOIUrl":"https://doi.org/10.1109/IITSI.2009.50","url":null,"abstract":"The characteristics of X-ray testing image are analyzed and an edge detection algorithm based on the multi-scale and multi-resolution of wavelet transform is proposed. According to the propagation of modulus maximum under different scales and the relationship between wavelet transform and Lipschitz exponent, the local maxima in vertical, horizontal and diagonal directions are detected by quadratic B-spline and Mallat algorithm was used in wavelet decomposition to determine defect edges. The experiment results prove that the algorithm of edge detection works fine the X-ray images.","PeriodicalId":308774,"journal":{"name":"2009 Second International Symposium on Intelligent Information Technology and Security Informatics","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128376894","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":"Artificial-Society-Based Classroom Behavior Dynamic Research","authors":"Lijun Wang, Chun-xiao Zhao","doi":"10.1109/IITSI.2009.47","DOIUrl":"https://doi.org/10.1109/IITSI.2009.47","url":null,"abstract":"This paper introduces the concept and framework of artificial classroom (AC) for the first time by employing artificial societies. Our solution is to use the artificial society approach for modeling artificial classroom. In the artificial society approach, agent-based simulation is used to explore and understand classroom misbehaviors issues. Student agents are selected as three kinds of typical agents and actions of the agents such as communicating, affecting and changing are all designed in detail. Thus, interactions among various agents and between agents and their environment are realized. Using NetLogo multi-agent platform, simulation programs of the model are developed. The simulation results reproduce the emergent pattern in time space and physical space.","PeriodicalId":308774,"journal":{"name":"2009 Second International Symposium on Intelligent Information Technology and Security Informatics","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131517494","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}
Jun Wu, Anastasiya Olesnikova, Chi-Hwa Song, W. Lee
{"title":"The Development and Application of Decision Tree for Agriculture Data","authors":"Jun Wu, Anastasiya Olesnikova, Chi-Hwa Song, W. Lee","doi":"10.1109/IITSI.2009.10","DOIUrl":"https://doi.org/10.1109/IITSI.2009.10","url":null,"abstract":"With the rapid increase of the world’s population, the drastic changes in world’s food supply, and the limitation of land resources, the pressure for agriculture is greater than ever before. With the development of AI theories and technologies, the study in the classification of agriculture data becomes more advanced and intellectualized. This paper mainly discusses a specific decision tree classifier which is used to predict and classify agriculture data. It is capable of dealing with both complete data and incomplete data. So that it can be applied into the classification problem for all kinds of agriculture data sets. The experiments are designed to prove the advantage of the proposed algorithm.","PeriodicalId":308774,"journal":{"name":"2009 Second International Symposium on Intelligent Information Technology and Security Informatics","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131447481","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 Novel Intrusion Detection Architecture Based on Adaptive Selection Event Triggering for Mobile Ad-hoc Networks","authors":"Chuan-xiang Ma, Z. Fang","doi":"10.1109/IITSI.2009.54","DOIUrl":"https://doi.org/10.1109/IITSI.2009.54","url":null,"abstract":"Due to resource limitation, it is an optimum solution for intrusion detection in mobile Ad-hoc networks (MANETs) that all nodes investigate system and user activities while a subset of network nodes are selected as monitoring nodes to monitor and detect network packets. In this paper, a novel intrusion detection architecture for energy-constrained mobile Ad-hoc networks is proposed, in which the network detection module is optional. Monitoring nodes are selected by activating the network detection model to work. A selection scheme of monitoring nodes called Event Triggering Based Adaptive Selection (ETBAS) is also proposed, which introduces the mechanism of monitoring states and the method of event triggering. Triggering events, for example, a node has been voted to be a monitoring node by its neighbors, the battery power of a monitoring node has consumed to a threshold, or the networks topology has changed, can activate a non-monitoring node, or make a monitoring node fall asleep. High connectivity and energy resource are balanced in ETBAS for adaptive selection scheme, which is adaptable to dynamically changing networks and enhances the network lifetime.","PeriodicalId":308774,"journal":{"name":"2009 Second International Symposium on Intelligent Information Technology and Security Informatics","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116825808","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":"Strengthening Buffer Operator Close to the Law of Indices and its Properties","authors":"Qin Wan, Yong Wei","doi":"10.1109/IITSI.2009.48","DOIUrl":"https://doi.org/10.1109/IITSI.2009.48","url":null,"abstract":"Construct one kind of new strengthening buffer operator which is close to the law of indices, and the examples have shown that the new strengthening buffer operator can enhance the forecasting simulation precision of GM model in shock disturbed system. When disturbance from the factor of the shock disturbed system affect to the primary data, then can use the new strengthening buffer operator to eliminate it. The strengthening new buffer operator has certain usability and validity. This paper provides methods for solving the contradiction between quantitative forecasting result and qualitative analysis conclusion","PeriodicalId":308774,"journal":{"name":"2009 Second International Symposium on Intelligent Information Technology and Security Informatics","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126208302","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":"Fast Rendering Algorithm of Underwater Optical Effect","authors":"Bo Qin, Lina Cui, Cui Xie","doi":"10.1109/IITSI.2009.44","DOIUrl":"https://doi.org/10.1109/IITSI.2009.44","url":null,"abstract":"Underwater optical effect simulation is an important component of simulating underwater scene. This paper will present a fast rendering algorithm of underwater optical effect based on Iwasak′s method. It simplifies the illumination volume to reduce the light calculation and uses the Gouraud shading method to render each side of every illumination volume. The experiments show that it can reduce the CPU calculation time and increase the rendering speed. The rendering results get a higher frame-rate with better quality.","PeriodicalId":308774,"journal":{"name":"2009 Second International Symposium on Intelligent Information Technology and Security Informatics","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121571050","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}