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

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Forecasting Stock Returns Based on Spline Wavelet Support Vector 基于样条小波支持向量的股票收益预测
2009 International Conference on Computational Intelligence and Natural Computing Pub Date : 2009-06-06 DOI: 10.1109/CINC.2009.243
Lingbing Tang, Huan-Ye Sheng
{"title":"Forecasting Stock Returns Based on Spline Wavelet Support Vector","authors":"Lingbing Tang, Huan-Ye Sheng","doi":"10.1109/CINC.2009.243","DOIUrl":"https://doi.org/10.1109/CINC.2009.243","url":null,"abstract":"Stock returns forecast is vital important in finance to reduce risk and take better decisions. This paper propose a spline wavelet kernel for support vector machine (SVM), called spline wavelet support vector machine (SWSVM), to model nonstationary financial time series. The SWSVM is obtained by incorporating the spline wavelet theory into SVM. Because spline wavelet function can yield features that describe of the stock time series both at various locations and at varying time granularities, the SWSVM can forecast stock returns accurately. The applicability and validity of spline wavelet support vector machine (SWSVM) for stock returns forecast were analyzed through experiments on real-world stock data. It appears that the spline wavelet kernel perform better than the Gaussian kernel.","PeriodicalId":173506,"journal":{"name":"2009 International Conference on Computational Intelligence and Natural Computing","volume":"47 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":"123372627","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: 3
Decoupling Control Using a PSO-Based Reinforcement Learning 基于粒子群的强化学习解耦控制
2009 International Conference on Computational Intelligence and Natural Computing Pub Date : 2009-06-06 DOI: 10.1109/CINC.2009.261
W. Xin, Yang Chun-hua, Qin Bin
{"title":"Decoupling Control Using a PSO-Based Reinforcement Learning","authors":"W. Xin, Yang Chun-hua, Qin Bin","doi":"10.1109/CINC.2009.261","DOIUrl":"https://doi.org/10.1109/CINC.2009.261","url":null,"abstract":"In this paper an intelligent decoupling control architecture using evolutionary reinforcement learning (IDCERL) is presented. The IDCERL utilizes an adaptive critic to estimate the decoupling performance, and a TSK fuzzy neural network (TSFN) to generate the decoupling action. By making use of the global optimization capability of particle swarm optimization (PSO), the IDCERL can solve the local minima problem in traditional actor-critic reinforcement learning. The IDCERL utilize a plant model to accelerate the convergence speed and void the possible risks of large disturbance of action generated by PSO global search. Proposed control strategy can reduce the controller developing time by incorporating prior knowledge in a fuzzy neural network form. The application for control system of collector gas pressure of coke ovens shows its validity.","PeriodicalId":173506,"journal":{"name":"2009 International Conference on Computational Intelligence and Natural Computing","volume":"37 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":"121301132","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: 3
Some Characterizations about 4-band Symmetric Cardinal Orthogonal Scaling Function 关于四波段对称基数正交标度函数的一些性质
2009 International Conference on Computational Intelligence and Natural Computing Pub Date : 2009-06-06 DOI: 10.1109/CINC.2009.41
Guochang Wu, Yanpei Zhao
{"title":"Some Characterizations about 4-band Symmetric Cardinal Orthogonal Scaling Function","authors":"Guochang Wu, Yanpei Zhao","doi":"10.1109/CINC.2009.41","DOIUrl":"https://doi.org/10.1109/CINC.2009.41","url":null,"abstract":"The 4-band symmetric cardinal orthogonal scaling function with compact support is of interest in several applications. In this paper, we provide some characterizations of the 4-band symmetric cardinal orthogonal scaling function. We generalize some results of the symmetric cardinal orthogonal scaling function from the 2-band case to the 4-band case. Also, we find some new results.","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":"114188510","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
Secret Image Sharing with Reversible Steganography 秘密图像共享与可逆隐写
2009 International Conference on Computational Intelligence and Natural Computing Pub Date : 2009-06-06 DOI: 10.1109/CINC.2009.249
Chinchen Chang, Pei-Yu Lin, Chi-Shiang Chan
{"title":"Secret Image Sharing with Reversible Steganography","authors":"Chinchen Chang, Pei-Yu Lin, Chi-Shiang Chan","doi":"10.1109/CINC.2009.249","DOIUrl":"https://doi.org/10.1109/CINC.2009.249","url":null,"abstract":"The significant essential of secret image sharing approaches is that the revealed content of the secret image must be lossless. Moreover, the distorted stego images can be reverted to the original cover image. In order to achieve these purposes, we first transform the secret pixels into the m-ary notational system. Then, the information data used to reconstruct original pixels from camouflaged pixels are calculated. The information data and transformed secret data are shared using the (t, n)-threshold sharing scheme. In this way, we can retrieve the lossless secret image and reverse the stego image to the original image. According to the experiments, the shadows can be successfully camouflaged in the cover image, and the stego images have satisfactory quality. Moreover, our scheme allows for a large capacity of embedded secret data.","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":"123867816","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: 11
Design of Incentive Mechanism for Independent Directors Based on Monitoring Mechanism under Asymmetric Information Condition 信息不对称条件下基于监督机制的独立董事激励机制设计
2009 International Conference on Computational Intelligence and Natural Computing Pub Date : 2009-06-06 DOI: 10.1109/CINC.2009.254
Xu Yan-li
{"title":"Design of Incentive Mechanism for Independent Directors Based on Monitoring Mechanism under Asymmetric Information Condition","authors":"Xu Yan-li","doi":"10.1109/CINC.2009.254","DOIUrl":"https://doi.org/10.1109/CINC.2009.254","url":null,"abstract":"The incentive mechanism for independent directors has yet to be established so far. Through mathematical models and game theory, this paper analyzes the optimal incentive contracts between stockholders and independent directors under asymmetric information condition in order to solve the problems in establishing incentive mechanism for independent directors. Supervision mechanism is introduced and analyzed in the design of incentive mechanism. It expands the theoretical frame for incentive mechanism. The results are as follows: Supervision mechanism is related and complementary with incentive mechanism. Both can encourage or guide the agent to work hard towards common goals. Therefore, the function of the incentive mechanism and the supervision mechanism should be considered simultaneously in the design of incentive contract. Introduction of supervision mechanism into incentive mechanism not only results in theoretical innovation, but also has great application value in practice.","PeriodicalId":173506,"journal":{"name":"2009 International Conference on Computational Intelligence and Natural Computing","volume":"5 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":"125302468","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
Inexact Parallel Relaxed Multisplitting Algorithm for Linear Complementarity Problem 线性互补问题的非精确并行松弛多分裂算法
2009 International Conference on Computational Intelligence and Natural Computing Pub Date : 2009-06-06 DOI: 10.1109/CINC.2009.158
B. Duan, Xiaoping Zhu, Jiaoyu Wu
{"title":"Inexact Parallel Relaxed Multisplitting Algorithm for Linear Complementarity Problem","authors":"B. Duan, Xiaoping Zhu, Jiaoyu Wu","doi":"10.1109/CINC.2009.158","DOIUrl":"https://doi.org/10.1109/CINC.2009.158","url":null,"abstract":"In this paper, the authors ¿rst set up the inexact parallel relaxed multisplitting Algorithm for solving the linear complementarity problems, which is based on the inexact splitting method, parallel computation and the multisplitting method. This new Algorithm provides a speci¿c realization for the multisplitting method and generalizes many existing matrix splitting methods for linear complementarity problems. And then, the global convergence theory of this new Algorithm is proved when the coef¿cient matrix is an H−matrix with positive diagonal elements. Last, a speci¿c iteration form for this inexact multisplitting Algorithm is presented, where the inner iterations are implemented through a matrix splitting method. Convergence properties for this speci¿c form are analyzed.","PeriodicalId":173506,"journal":{"name":"2009 International Conference on Computational Intelligence and Natural Computing","volume":"202 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":"122447289","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
Approaches to Decision Inference Rules Based on Concept Lattices 基于概念格的决策推理规则方法
2009 International Conference on Computational Intelligence and Natural Computing Pub Date : 2009-06-06 DOI: 10.1109/CINC.2009.181
Guofang Qiu
{"title":"Approaches to Decision Inference Rules Based on Concept Lattices","authors":"Guofang Qiu","doi":"10.1109/CINC.2009.181","DOIUrl":"https://doi.org/10.1109/CINC.2009.181","url":null,"abstract":"Four kinds of basic decision rule sets are respectively produced from the formal concept lattice, the dual formal concept lattice, the object-oriented concept lattice and the attribute-oriented concept lattice in a formal context. Based on these sets, two types of decision inferences are established via an inclusion degree. The corresponding decisions by inferences are proved to be the lower and the upper approximated decisions. Thus total decision rules described as the lower and the upper approximated decision rules are obtained. And they are accordant and consistent with the basic decision rule sets.","PeriodicalId":173506,"journal":{"name":"2009 International Conference on Computational Intelligence and Natural Computing","volume":"37 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":"122787501","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
The Research on Axial Vibration of Drill String with Delphi 钻柱轴向振动的Delphi研究
2009 International Conference on Computational Intelligence and Natural Computing Pub Date : 2009-06-06 DOI: 10.1109/CINC.2009.85
Han Chunjie, Yan Tie
{"title":"The Research on Axial Vibration of Drill String with Delphi","authors":"Han Chunjie, Yan Tie","doi":"10.1109/CINC.2009.85","DOIUrl":"https://doi.org/10.1109/CINC.2009.85","url":null,"abstract":"Drill string vibration is a very prevalent phenomena, it does great effect to drilling engineering, drill string resonance is the main reason that causes the drill string fatigue. In this paper the drill string is object that is studied, the axial vibration is analyzed for the total system of drill string. The model of axial vibration is established, the rule about axial vibration of drill string is obtained, the nature frequency of axial vibration is found out by Delphi. Then, the rule can be used in the oil field for the drilling worker, the rule can provide reliable theory for decreasing drill fatigue and optimizing drilling parameter.","PeriodicalId":173506,"journal":{"name":"2009 International Conference on Computational Intelligence and Natural Computing","volume":"182 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":"133567980","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
An Effective Signal Processing Method to Musical Information Retrieval 音乐信息检索中一种有效的信号处理方法
2009 International Conference on Computational Intelligence and Natural Computing Pub Date : 2009-06-06 DOI: 10.1109/CINC.2009.22
L. Peng, Zhou Mingquan, W. Xuesong, Li Nansha
{"title":"An Effective Signal Processing Method to Musical Information Retrieval","authors":"L. Peng, Zhou Mingquan, W. Xuesong, Li Nansha","doi":"10.1109/CINC.2009.22","DOIUrl":"https://doi.org/10.1109/CINC.2009.22","url":null,"abstract":"In this paper, an effective acoustic signal processing method has been presented in research of Musical Information Retrieval (MIR). Firstly, the raw acoustic signal was pretreated by a adaptive wavelet soft-threshold of gain factor and teager energy operator (AWSTD_GF&TEO), then it needs to extract the fundamental frequency form it. Secondly, proposed a new effective \"cabinet\" method to filter the waveform, after that, the waveform is available compared with the one unfiltered, at last, implemented the retrieval operations with an improved melody representation method and string fuzzy matching method. The evaluation result shows that the AWSTD_GF&TEO and the new \"cabinet\" method could help to retrieval the object more accurate.","PeriodicalId":173506,"journal":{"name":"2009 International Conference on Computational Intelligence and Natural Computing","volume":"7 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":"132770472","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
Knowledge-increasable Neural Network Group and its Control Application 知识递增神经网络群及其控制应用
2009 International Conference on Computational Intelligence and Natural Computing Pub Date : 2009-06-06 DOI: 10.1109/CINC.2009.9
Jin Lv, H. Fan, Xiang-mo Zhao
{"title":"Knowledge-increasable Neural Network Group and its Control Application","authors":"Jin Lv, H. Fan, Xiang-mo Zhao","doi":"10.1109/CINC.2009.9","DOIUrl":"https://doi.org/10.1109/CINC.2009.9","url":null,"abstract":"Aiming at the complex dynamic feature of large ship, an intelligent control structure based on Library-similar Knowledge-increasable Neural Network Group is presented. This compounded control structure using the dynamic knowledge-increasable learning capability of the neural network groups, solve the problems of online identification and online design of the controller, so that the high precise output tracking control of uncertain nonlinear large ship can be realized. Simulating results show that it is feasible and effective.","PeriodicalId":173506,"journal":{"name":"2009 International Conference on Computational Intelligence and Natural Computing","volume":"32 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":"133253169","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
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