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2009 International Conference on Computational Intelligence and Natural Computing最新文献

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Nude Image Detection Based on SVM 基于SVM的裸体图像检测
2009 International Conference on Computational Intelligence and Natural Computing Pub Date : 2009-06-06 DOI: 10.1109/CINC.2009.148
Xin-Lu Wang, Xiao-juan Li, Xiao-bo Liu
{"title":"Nude Image Detection Based on SVM","authors":"Xin-Lu Wang, Xiao-juan Li, Xiao-bo Liu","doi":"10.1109/CINC.2009.148","DOIUrl":"https://doi.org/10.1109/CINC.2009.148","url":null,"abstract":"On the Internet, the nude images caused the spread of a large number of social problems, how to identify the nude image accurately is a problem needing to be solved urgently. Therefore, we integrate both image processing method and support vector machines (SVM), this paper studies a new and enhanced approach on recognition of nude image, namely, combine a face detection model, skin color model and texture model, extract six nude image feature vectors. Additionally, some important factors of SVM are fixed by experiments, such as the training set, kernel function and the cost. The experimental results demonstrate that performing SVM-based nude image detective classification more effective in that it improves the prediction accuracies at the same time.","PeriodicalId":173506,"journal":{"name":"2009 International Conference on Computational Intelligence and Natural Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129722077","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: 6
Design of Collaborate Schedule for Object Detection in Wireless Sensor Networks 无线传感器网络中目标检测协同调度设计
2009 International Conference on Computational Intelligence and Natural Computing Pub Date : 2009-06-06 DOI: 10.1109/CINC.2009.199
Shuo Xiao, Kaicheng Li, Xueye Wei, Yu Wang
{"title":"Design of Collaborate Schedule for Object Detection in Wireless Sensor Networks","authors":"Shuo Xiao, Kaicheng Li, Xueye Wei, Yu Wang","doi":"10.1109/CINC.2009.199","DOIUrl":"https://doi.org/10.1109/CINC.2009.199","url":null,"abstract":"Wireless sensor networks (WSNs) have attracted a lot of research attention. WSNs contain a large number of nodes that are capable of sensing, processing and transmitting environmental information. In this paper, object detection has been studied. For WSNs are composed of power-restrained nodes, so energy-efficiency is a key concern in WSNs. Balancing object detection performance and network lifetime is a challenging in sensor networks. Base on the theoretical analysis, we propose a novel energy-aware wake up schedule that significantly prolongs the life of WSNs and maintain the detection performance. Simulation results confirm with the theoretical analysis and demonstrate the advantage of EAS over previous proposed methods.","PeriodicalId":173506,"journal":{"name":"2009 International Conference on Computational Intelligence and Natural Computing","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130123670","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
The Study of Teaching Reform Project Pool Management System in Applied College 应用型高校教学改革项目库管理系统研究
2009 International Conference on Computational Intelligence and Natural Computing Pub Date : 2009-06-06 DOI: 10.1109/CINC.2009.26
Chao Wang, Xing Fang, Samanta Yang, B. Huang
{"title":"The Study of Teaching Reform Project Pool Management System in Applied College","authors":"Chao Wang, Xing Fang, Samanta Yang, B. Huang","doi":"10.1109/CINC.2009.26","DOIUrl":"https://doi.org/10.1109/CINC.2009.26","url":null,"abstract":"The reasons of applying for teaching reform projects and the current situation are introduced in this paper, the teaching reform project pool management system is given and the operation methods with operation rules are analyzed which are helpful to improve the applied college teaching management quality.","PeriodicalId":173506,"journal":{"name":"2009 International Conference on Computational Intelligence and Natural Computing","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129125432","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
Large Deviation on Random Sums for a Double Type-insurance Risk Model 双类型保险风险模型随机和的大偏差
2009 International Conference on Computational Intelligence and Natural Computing Pub Date : 2009-06-06 DOI: 10.1109/CINC.2009.221
X. Zhan, Li Yu
{"title":"Large Deviation on Random Sums for a Double Type-insurance Risk Model","authors":"X. Zhan, Li Yu","doi":"10.1109/CINC.2009.221","DOIUrl":"https://doi.org/10.1109/CINC.2009.221","url":null,"abstract":"A double-type-insurance risk model with heavy tails has been defined and studied. A further investigation into the large deviation on random sums under the distribution of dominated variation (D class) is presented in this paper.","PeriodicalId":173506,"journal":{"name":"2009 International Conference on Computational Intelligence and Natural Computing","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131977772","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
An Intelligent Algorithm Based on Grid Searching and Cross Validation and its Application in Population Analysis 基于网格搜索和交叉验证的智能算法及其在种群分析中的应用
2009 International Conference on Computational Intelligence and Natural Computing Pub Date : 2009-06-06 DOI: 10.1109/CINC.2009.178
Yangu Zhang, Saiping Chen, Y. Wan
{"title":"An Intelligent Algorithm Based on Grid Searching and Cross Validation and its Application in Population Analysis","authors":"Yangu Zhang, Saiping Chen, Y. Wan","doi":"10.1109/CINC.2009.178","DOIUrl":"https://doi.org/10.1109/CINC.2009.178","url":null,"abstract":"Population statistic and forecast is important basis that government establishes correlative policy, population’s all characteristic has strong non-linear speciality because of all kinds of effects. A cross validation optimized parameter least support vector machine method of population statistic and forecast is presented aiming at bad precision and lack of rationality of all approximate model at present. Complicated and strong nonlinear population characteristic relation is simulated by network design and conformation of the least square support vector machine learning algorithm and selecting the optimized support vector machine parameters by the method of grid searching and cross validation. The model is HverifiedH by taking population growth rate HforH example, cross validation optimized parameter least support vector machine algorithm has strong ability of nonlinear mapping and self-learning, it avoids availably phenomenon of partial minimum and overfitting, the future population problem can be accurately calculated and judged , it gains high precision by comparing numerical value of network output with fitting value and numerical real value. It provides a new artificial intelligent approach for population analysis.","PeriodicalId":173506,"journal":{"name":"2009 International Conference on Computational Intelligence and Natural Computing","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131005795","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: 2
Improvement of Association Rules Mining Algorithm in Wireless Network Intrusion Detection 无线网络入侵检测中关联规则挖掘算法的改进
2009 International Conference on Computational Intelligence and Natural Computing Pub Date : 2009-06-06 DOI: 10.1109/CINC.2009.19
Ye Changguo, Zhang Qin, Zhou Jingwei, Wei Nianzhong, Zhu Xiaorong, Wang Tailei
{"title":"Improvement of Association Rules Mining Algorithm in Wireless Network Intrusion Detection","authors":"Ye Changguo, Zhang Qin, Zhou Jingwei, Wei Nianzhong, Zhu Xiaorong, Wang Tailei","doi":"10.1109/CINC.2009.19","DOIUrl":"https://doi.org/10.1109/CINC.2009.19","url":null,"abstract":"This paper, first analyzes the method of wireless network intrusion detection, presents a wireless network intrusion detection algorithm based on association rule mining. The application of fuzzy association rules in the wireless network intrusion detection is mainly discussed, and the steps to implement the algorithm are expressed. A comparative analysis with the classical algorithm Apriori is made by experiment. The results show that wireless network intrusion detecting using fuzzy association rules mining algorithm is a feasible method.","PeriodicalId":173506,"journal":{"name":"2009 International Conference on Computational Intelligence and Natural Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130461511","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: 13
Distributed Fusion Estimation Based on Pseudo-measurement for Multi-sensor System 基于伪测量的多传感器系统分布式融合估计
2009 International Conference on Computational Intelligence and Natural Computing Pub Date : 2009-06-06 DOI: 10.1109/CINC.2009.95
Jin Xue-bo, Du Jing-jing, Wang Lei-lei
{"title":"Distributed Fusion Estimation Based on Pseudo-measurement for Multi-sensor System","authors":"Jin Xue-bo, Du Jing-jing, Wang Lei-lei","doi":"10.1109/CINC.2009.95","DOIUrl":"https://doi.org/10.1109/CINC.2009.95","url":null,"abstract":"By considering the relation between local fusion estimation and fusion center, in this paper the estimation from local fusion nodes is regarded as a pseudo-measurement. Then the distributed estimation algorithm is turned to be two-level centralized fusion estimation and the new optimal distributed fusion estimation algorithm is obtained with Kalman filtering form, which in general only centralized estimation method has. Simulations show the developed algorithm has the excellent estimation performance. By the developed algorithm, the distributed multisensor system can be unified with centralized system and make it possible that applying the abundant research result of centralized system to distributed multisensor system.","PeriodicalId":173506,"journal":{"name":"2009 International Conference on Computational Intelligence and Natural Computing","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127955459","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
Research on Control Problem of PenduBot Based on PSO Algorithm 基于粒子群算法的PenduBot控制问题研究
2009 International Conference on Computational Intelligence and Natural Computing Pub Date : 2009-06-06 DOI: 10.1109/CINC.2009.132
Shaoqiang Yuan, Dong Wang, Xingshan Li
{"title":"Research on Control Problem of PenduBot Based on PSO Algorithm","authors":"Shaoqiang Yuan, Dong Wang, Xingshan Li","doi":"10.1109/CINC.2009.132","DOIUrl":"https://doi.org/10.1109/CINC.2009.132","url":null,"abstract":"PenduBot is a new experiment object in the control theory and a typical representation in the underactuated robot, so it is the research focus of control and robot domain. It is known for its strongly nonlinear and naturally unstable properties. To stabilize the PenduBot and verify the control abilities of the algorithm on strongly nonlinear and naturally unstable properties, the thesis presents the purpose that the state-feedback matrixes can be optimized by new bionics algorithm PSO. Based on the introduction of standard PSO algorithm, how to select the position and velocity evolution equations parameters and fitness function became a great emphasis. Next, the simulations were done on the linearized PenduBot model in MATLAB environment by PSO and LQR algorithm separately, and the results were compared. Finally, the comparison results proved the PSO advantages. The expected goal was achieved.","PeriodicalId":173506,"journal":{"name":"2009 International Conference on Computational Intelligence and Natural Computing","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129000477","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: 9
A Self-adapting Algorithm for Identifying Rheology Model and Its Parameters of Rock Mass 岩体流变模型及其参数识别的自适应算法
2009 International Conference on Computational Intelligence and Natural Computing Pub Date : 2009-06-06 DOI: 10.1109/CINC.2009.39
Bing-Rui Chen, Xiating Feng, Chengxiang Yang
{"title":"A Self-adapting Algorithm for Identifying Rheology Model and Its Parameters of Rock Mass","authors":"Bing-Rui Chen, Xiating Feng, Chengxiang Yang","doi":"10.1109/CINC.2009.39","DOIUrl":"https://doi.org/10.1109/CINC.2009.39","url":null,"abstract":"As it is difficult to previously determine rockmass rheology constitutive model using phenomena methods of mechanics, so a new self-adapting system identification method, a hybrid genetic programming (GP) with the chaos-genetic algorithm(CGA) based on self-rheological characteristic of rock mass, is proposed. Genetic programming is used for exploring the model’s structure and the chaos-genetic algorithm is produced to identify parameters (coefficients) in the tentative model. The optimal rheological model is determined by mechanical and rheological characteristic, important expertise ect and can describe rheological behavior of identified rock mass perfectly. The assistant tunnel B of Jinping-2 hydropower station is used as an example for verifying the proposed method. The results show that the algorithm is feasible and has great potential in finding new rheological models.","PeriodicalId":173506,"journal":{"name":"2009 International Conference on Computational Intelligence and Natural Computing","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125511142","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
The Construction of Transactions for Web Usage Mining 面向Web使用挖掘的事务构建
2009 International Conference on Computational Intelligence and Natural Computing Pub Date : 2009-06-06 DOI: 10.1109/CINC.2009.101
Yan Li, Boqin Feng
{"title":"The Construction of Transactions for Web Usage Mining","authors":"Yan Li, Boqin Feng","doi":"10.1109/CINC.2009.101","DOIUrl":"https://doi.org/10.1109/CINC.2009.101","url":null,"abstract":"A data preprocessing system for constructing the transactions in web usage mining is presented. To implement transaction identification, the user sessions and the user access paths are extracted from the web access log and missing information is appended. These tasks are accomplished with the application of the referer-based method, which is an effective solution to the problems introduced by using proxy servers, local caching and firewall. Meanwhile, the reference length of accessed pages is calculated with the consideration of the time spent on data transfer over internet. Then two kinds of transactions are defined, i.e. travel-path transactions and content-only transactions. These two kinds of transactions are constructed by the maximal forward references (MFR) algorithm and the reference length (RL) algorithm, respectively. As verified by practical web access log, it is shown that the transactions can be efficiently identified while the reliability of the original web access data is obviously improved for the further researches.","PeriodicalId":173506,"journal":{"name":"2009 International Conference on Computational Intelligence and Natural Computing","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125552940","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: 28
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