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2010 Second International Conference on Computational Intelligence and Natural Computing最新文献

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An improved PCNN model and a new removing algorithm of salt and pepper noise 一种改进的PCNN模型及椒盐噪声去除新算法
Yan Wu, Bing Xu, Xiao-Yue Bian
An improved PCNN model-PCNN with Positive and Negative Firing, PCNNPNF-is proposed, and also put forward a de-noising algorithm based on the time matrix of PCNNPNF. The biggest improvement is that the neuron's output of improved PCNN has three states: positive firing, negative firing and no firing, while PCNN only has two states: firing and no firing. Experimental results show that the de-noising algorithm based on PCNNPNF can quickly find the two kinds of pulse noises, remove these noises, and reserve more information than PCNN.
提出了一种改进的PCNN模型PCNNPNF- Positive and Negative Firing,并提出了一种基于PCNNPNF时间矩阵的去噪算法。最大的改进是改进后的PCNN神经元输出有正放电、负放电和不放电三种状态,而PCNN只有放电和不放电两种状态。实验结果表明,基于PCNNPNF的去噪算法能够快速发现并去除两种脉冲噪声,并且比PCNN保留更多的信息。
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引用次数: 1
Solving multi-class traffic assignment problem with genetic algorithm 用遗传算法求解多类交通分配问题
Guoqiang Zhang, Jun Chen
Multi-class traffic assignment problem is an extension of the classic static traffic assignment problem with user equilibrium. It provides a more correct and detailed description of traffic patterns and trends. Because of the complexity of the models for multi-class traffic assignment problem, which are usually defined by a non-monotonic cost operator, neither the uniqueness nor the stability of a feasible solution can be guaranteed and the traditional nonlinear optimization algorithms are therefore invalid. Based upon the mathematic characteristics of multiclass traffic assignment problem, genetic algorithm has been adopted for its solution. To ensue efficiency of the algorithm, the genetic operators such as crossover and mutation were designed specifically, as expressed by Equation 11, 12 and 13, so that constrains expressed by Equation 5 can be satisfied. With a test road network as an example, as shown in Figure 1, the new genetic algorithm has been proved to be very effective.
多类流量分配问题是经典静态用户均衡流量分配问题的扩展。它提供了对流量模式和趋势的更正确和详细的描述。多类交通分配问题通常由非单调代价算子定义,由于模型的复杂性,无法保证可行解的唯一性和稳定性,传统的非线性优化算法失效。针对多类交通分配问题的数学特点,采用遗传算法进行求解。为保证算法的高效性,对交叉、突变等遗传算子进行了具体设计,如式11、12、13所示,满足式5所示的约束条件。以一个测试路网为例,如图1所示,新的遗传算法被证明是非常有效的。
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引用次数: 10
Design of sewage flow remote monitoring system over GPRS network 基于GPRS网络的污水流量远程监控系统设计
Yanmin Ning, Dean Zhao, Jiajun Guan, Shichang Gong
In this paper, a new sewage flow remote monitoring system over General Packet Radio Service (GPRS) is presented, which monitors the sewage flow parameter remotely in real time. In the proposed system, GPRS network is adopted as the wireless sensor network, and the data between the slave computer and the remote terminal are transmitted via the GPRS and Internet networks. Finally in the remote terminal, the Winsock control of Visual Basic 6.0 is responsible for displaying, storing and analyzing the data of the sewage flow. The system is easy to implement and has a high degree of automation, by which the acquisition, transmission and processing of the sewage flow data can be achieved in wireless, networked and intelligent manners.
提出了一种基于通用分组无线业务(GPRS)的污水流量远程监控系统,实现了对污水流量参数的远程实时监控。本系统采用GPRS网络作为无线传感器网络,从机与远程终端之间的数据通过GPRS网络和Internet网络进行传输。最后在远程终端由Visual Basic 6.0的Winsock控件负责对污水流量数据进行显示、存储和分析。该系统实现简单,自动化程度高,可以实现污水流量数据的采集、传输和处理的无线化、网络化和智能化。
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引用次数: 1
The influence of achievement goal orientation, self-efficacy and task difficulty on JOL 成就目标取向、自我效能感和任务难度对JOL的影响
Shuhua Su, Gongxiang Chen
In order to investigate the influence of achievement goal orientation, self-efficacy and task difficulty on judgment of learning (JOL), we selected 96 senior high School students that were investigated through RJR paradigm and materials (meaningful and meaningless associated Chinese word -pairs) in this study. The results showed that: (1) Achievement goal orientation, self-efficacy and material factor had prominent influence on judgment of learning. (2) Achievement goal orientation and self-efficacy had different interactive influence on judgment of learning. (3)The testing of mediating effect indicated that self-efficacy was a mediator factor between achievement goal orientation and judgment of learning. So we draw the conclusions that achievement goal orientation, self-efficacy and task difficulty affect JOL.
为了探讨成就目标取向、自我效能感和任务难度对学习判断的影响,本研究以96名高中生为研究对象,采用RJR范式和相关材料(有意义和无意义的汉语相关词对)进行调查。结果表明:(1)成就目标取向、自我效能感和物质因素对学习判断有显著影响。(2)成就目标取向和自我效能感对学习判断有不同的交互影响。(3)中介效应检验表明,自我效能感是成就目标取向与学习判断之间的中介因素。因此,我们得出了成就目标取向、自我效能感和任务难度对工作效率有影响的结论。
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引用次数: 1
The research in public transit scheduling based on the improved genetic simulated annealing algorithm 基于改进遗传模拟退火算法的公共交通调度研究
Chang-sheng Zhu, Hongmei Huang, Yuan Yuan, Qing-rong Wang
In this work,we set up public transit planning model by analysising of vehicle dispatching and taking both interest of bus company and passenger into consideration. using the improved genetic simulated annealing algorithm(the improved GA-SA) to carry out optimization for public transit dispatching model,and overcomes the problems such as evolution is slow,precocious, local optimal solution and so on, it can find the approximate optimum solution, reliably, from the huge search space of scheduling optimization problem. intelligent scheduling optimization problem in the great search space to find reliable optimal solution or approximate optimal solution. Finally,we use MATLAB to carry on simulation experiment. the results show that the improved GA-SA has higher efficiency than traditional GA.
本文通过对车辆调度的分析,同时考虑公交公司和乘客的利益,建立了公共交通规划模型。利用改进的遗传模拟退火算法(改进GA-SA)对公交调度模型进行优化,克服了进化缓慢、早熟、局部最优解等问题,能够从调度优化问题巨大的搜索空间中可靠地找到近似最优解。智能调度优化问题在大搜索空间中寻找可靠的最优解或近似最优解。最后,利用MATLAB进行仿真实验。结果表明,改进遗传算法比传统遗传算法具有更高的效率。
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引用次数: 2
The intelligent logistics management system based on intelligent computing 基于智能计算的智能物流管理系统
J. Qian, Jianguo Zheng, Chaoqun Zhang
Traditionally, some common algorithms to optimize the integration of logistics resource are linear programming, dynamic programming, and etc., however, these algorithms can't well solve many complex optimization issues, especially nonlinear issues, because of the continuous growth of issue complexity. On the contrary, intelligent computing technology has many advantages in solving complex, nonlinear and multi-objective optimization issue. But, how to build intelligent logistics management system based on intelligent computing technology has become a challenge. This paper, focusing on the function and system structure of intelligent management platform, presents the design of intelligent logistics management system based on Global Positioning System (GPS), Geographic Information System (GIS), and intelligent computing. Finally, a sample model of using quantum genetic intelligent algorithm to solve transportation problem in the intelligent logistics management system is given.
传统上常用的物流资源整合优化算法有线性规划、动态规划等,但由于问题复杂性的不断增长,这些算法并不能很好地解决许多复杂的优化问题,特别是非线性问题。相反,智能计算技术在解决复杂、非线性和多目标优化问题方面具有许多优势。但是,如何构建基于智能计算技术的智能物流管理系统已成为一个挑战。本文围绕智能管理平台的功能和系统结构,提出了基于全球定位系统(GPS)、地理信息系统(GIS)和智能计算的智能物流管理系统的设计。最后,给出了在智能物流管理系统中应用量子遗传智能算法求解运输问题的示例模型。
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引用次数: 2
Performance analysis of spread spectrum communication system in fading enviornment and Interference 扩频通信系统在衰落环境和干扰下的性能分析
Xiaoping Tian, Sishijiu Dong, Yu Han
We analyze the performance of spread spectrum (SS) communication system in fading enviornment and interference based on simulation platform. Modules of the spread spectrum system and environment with interference and fading are simulated and modeled. Monte Carlo simulation experiments are done based on the spread spectrum communication simulation platform. Then the BER performance of spread spectrum communication simulation system over interference and fading channels are obtained from the simulation results. Theory analysis and simulation experiments show that SS technology can effectively combat interference and are adaptive to the fading environment.
基于仿真平台,分析了扩频通信系统在衰落环境和干扰下的性能。对扩频系统的模块和有干扰和衰落的环境进行了仿真和建模。在扩频通信仿真平台上进行了蒙特卡罗仿真实验。然后根据仿真结果得出了扩频通信仿真系统在干扰信道和衰落信道下的误码率性能。理论分析和仿真实验表明,该技术能有效地对抗干扰,对衰落环境具有较强的适应性。
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引用次数: 2
Feature selection method for facial representation using parzen-window density estimation 基于parzen窗密度估计的人脸表征特征选择方法
Heng Fui Liau, D. Isa
This paper proposes a feature selection method that aims to select an optimal feature subset to representing facial image from the point of view of minimizing the total error rate (TER) of the system. In this proposed approach, the genuine user score distribution and the imposter score distribution are modeled based on a Parzen-window density estimation to enable the direct estimation of total error rate (TER) as reflected by the area under the curve of the overlapping region of both distributions. Particle swarm optimization (PSO) is employed to search for feature subsets which are extracted from discrete cosine transform or principal component analysis that gives minimum TER and in the meantime to reduce the dimensionality of the feature set thereby reducing processing time.
本文提出了一种特征选择方法,从最小化系统的总错误率(TER)的角度出发,选择一个最优的特征子集来表示人脸图像。在该方法中,真实用户得分分布和冒名用户得分分布基于Parzen-window密度估计建模,从而可以直接估计总错误率(TER),这是由两种分布的重叠区域曲线下的面积反映出来的。采用粒子群算法(Particle swarm optimization, PSO)对离散余弦变换或主成分分析提取的特征子集进行搜索,使特征子集的TER最小,同时降低特征集的维数,从而减少处理时间。
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引用次数: 1
Identifying nuclear protein subcellular localization using feature dimension reduction method 特征降维法识别核蛋白亚细胞定位
Tong Wang, Qinghua Huang, Lihua Hu
The subcellular location of a protein is closely correlated to its function. Facing the deluge of protein sequences generated in the post-genomic age, it is necessary to develop useful machine learning tools to identify the protein subcellular localization. DR (Dimensional Reduction) method is one of most famous machine learning tools. Some researchers have begun to explore DR method for computer vision problems such as face recognition, few such attempts have been made for classification of high-dimensional protein data sets. In this paper, DR method is employed to reduce the size of the features space. Comparison between linear DR methods (PCA and LDA) and nonlinear DR methods (KPCA and KLDA) is performed to predict subcellular localization of nuclear proteins. Experimental results thus obtained are quite encouraging, which indicate that the DR method is used effectively to deal with this complicated problem of viral proteins subcellular localization prediction. The overall jackknife success rate with KLDA is the highest relative to the other DR methods.
蛋白质的亚细胞位置与其功能密切相关。面对后基因组时代产生的大量蛋白质序列,有必要开发有用的机器学习工具来识别蛋白质的亚细胞定位。DR(降维)方法是最著名的机器学习工具之一。一些研究者已经开始探索DR方法在人脸识别等计算机视觉问题上的应用,但对于高维蛋白质数据集的分类研究还很少。本文采用DR方法减小特征空间的大小。比较了线性DR方法(PCA和LDA)和非线性DR方法(KPCA和KLDA)对核蛋白亚细胞定位的预测。实验结果令人鼓舞,表明DR方法可以有效地解决复杂的病毒蛋白亚细胞定位预测问题。与其他DR方法相比,KLDA的综合刀切成功率最高。
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引用次数: 0
Convergence of modified conjugate gradient methods without line search 修正共轭梯度法的收敛性
Bo Zhang
In this paper, a class of modified conjugate gradient methods are proposed, which have the following attractive properties: (1) the step length is determined by a formula; (2) the iterative direction is always a sufficient descent direction without utilizing the line search. Under the boundedness of the level set and the Lipschitz continuity of the underlying function, the proposed methods are global convergent. Some numerical results are given to illustrate the effectiveness of the proposed methods.
本文提出了一类改进的共轭梯度法,它具有以下吸引人的性质:(1)步长由公式确定;(2)不使用直线搜索,迭代方向始终是一个充分的下降方向。在水平集的有界性和底层函数的Lipschitz连续性下,所提方法是全局收敛的。数值结果表明了所提方法的有效性。
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引用次数: 2
期刊
2010 Second International Conference on Computational Intelligence and Natural Computing
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