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2009 International Workshop on Intelligent Systems and Applications最新文献

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LIS-No-Classification Wavelet Image Coding Algorithm Based on Lifting Scheme 基于提升方案的lis -无分类小波图像编码算法
Pub Date : 2009-05-23 DOI: 10.1109/IWISA.2009.5072941
Guowei Tang, G. Gu
For most coefficients of wavelet image are zero, SPIHT algorithm which divides the list of insignificant pixels(LIS) into type A and type B and carries out classification judgment to each node in the list leads to the time cost increasing to the encoder. This paper introduces a kind of wavelet base(V9/3) with human vision properties and lifting wavelet transform, cancels the classification procedure of LIS in SPIHT algorithm, merges the modified processing procedure of type B node with that of type A node, encodes the significant coefficients universally in accordance with the sequence of the spatial orientation tree from son generation to grandson generation. The experiment results show that the proposed algorithm improve the speed of encoding effectively while the visual effect of the reconstructed images is kept.
由于大多数小波图像的系数为零,SPIHT算法将不显著像素列表(LIS)划分为A类和B类,并对列表中的每个节点进行分类判断,导致编码器的时间成本增加。本文引入了一种具有人类视觉特性的小波基(V9/3),提升了小波变换,取消了SPIHT算法中LIS的分类过程,将修正后的B类节点处理过程与a类节点处理过程合并,按照空间方向树从子代到子代的顺序对显著系数进行了统一编码。实验结果表明,该算法在保持重构图像视觉效果的同时,有效地提高了编码速度。
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引用次数: 1
Local Information Preprocessing of Engineering Equipments Based on Rough Set 基于粗糙集的工程装备局部信息预处理
Pub Date : 2009-05-23 DOI: 10.1109/IWISA.2009.5072943
Jianhui Liu
Aiming at some foundational remote diagnosis bottleneck problem due to abundant out-of-order data, such as fault information transmission barrage, delay, in view of condition monitoring, fault prognostication and diagnosis, the thought and framework of local information preprocessing based on rough set are presented. After given out some correlative knowledge about rough set, information reduction algorithms of condition monitoring and fault diagnosis are described respectively, the validity of above two algorithms is also validated combining with brake system of concrete transport equipment. In conclusion, more application of rough set for fault diagnosis is discussed.
针对故障信息传输混乱、延迟等大量无序数据导致的基础远程诊断瓶颈问题,从状态监测、故障预测和诊断的角度出发,提出了基于粗糙集的局部信息预处理思想和框架。在给出粗糙集相关知识的基础上,分别描述了状态监测和故障诊断的信息约简算法,并结合混凝土输送设备制动系统验证了上述两种算法的有效性。最后,讨论了粗糙集在故障诊断中的更多应用。
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引用次数: 0
Enhancement of Radiograph Images Based on Chaos Optimization 基于混沌优化的x线图像增强
Pub Date : 2009-05-23 DOI: 10.1109/IWISA.2009.5072849
Yinjie Sun
How to select the parameters of high-frequency emphasis filtering (HFEF) in order to enhance radiograph images, this paper presents an enhancing method based on chaos optimization algorithms (COA). Based on the properties of ergodicity, stochastic property and regularity of chaos, the chaos optimization method can get global solution with low computational load. Firstly, an X-ray image is sharpened with HFEF, at the same time, the controllable and improved COA can optimize the parameters so that the optimal clarity of the image may be got, then the contrast of it is enhanced with histogram equalization to visually enhance the medical radiograph images to solve the questions: blurring and dark nature, which radiograph images generally tend to have. Experimental results show the proposed approach is effective and gets competitive visual effects.
本文提出了一种基于混沌优化算法(COA)的高频重点滤波(HFEF)增强方法。基于混沌的遍历性、随机性和规律性,混沌优化方法能以较低的计算量获得全局解。首先利用HFEF对x射线图像进行锐化,同时利用可控改进的COA对参数进行优化,获得最佳的图像清晰度,然后利用直方图均衡化对图像对比度进行增强,从视觉上增强医学x射线图像,解决x射线图像普遍存在的模糊和暗化问题。实验结果表明,该方法是有效的,能获得较好的视觉效果。
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引用次数: 1
Improvement of UKF Algorithm and Robustness Study UKF算法改进及鲁棒性研究
Pub Date : 2009-05-23 DOI: 10.1109/IWISA.2009.5072908
Zhongkai Mou, L. Sui
Iterated unscented Kalman filter (IUKF) algorithm has improved the unscented Kalman filter (UKF) and enhanced the performance of filter estimation by using Newton-Raphson iterative equation. This paper improves IUKF algorithm ulteriorly after detailedly analyzing principle of IUKF and its iterative equation, and proposes a new filtering algorithm with robustness-Improved IUKF. Then the performance of the new algorithm is validated by two experiments. The results show that the improved IUKF is more robust which can effectively resist the influence of measurement outlier.
迭代无气味卡尔曼滤波器(IUKF)算法是对无气味卡尔曼滤波器(UKF)的改进,利用牛顿-拉夫森迭代方程提高了滤波器估计的性能。本文在详细分析了IUKF的原理及其迭代方程的基础上,对IUKF算法进行了进一步改进,提出了一种新的具有鲁棒性的滤波算法——改进的IUKF。然后通过两个实验验证了新算法的性能。结果表明,改进后的IUKF具有更强的鲁棒性,能够有效抵抗测量异常值的影响。
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引用次数: 3
An Improved Method of Motion Detection Based on Temporal Difference 一种改进的基于时间差分的运动检测方法
Pub Date : 2009-05-23 DOI: 10.1109/IWISA.2009.5072718
Shui-gen Wei, Zhen Chen, Ming Li, Liang Zhuo
An improved method of motion detection based on temporal difference is proposed in this paper. This method could solve the general problem of holes being generated in moving object area when using temporal difference method. Firstly, an absolute differential image is calculated from two consecutive gray frames in image sequences. Secondly, the absolute differential image is filtered by low-pass filter, and translated into binary image. Thirdly, a number of binary images are calculated by some gray images in the image sequences. Finally, motion object region is extracted by arithmetic operations of pixels from binary images mentioned above. Experimental results show that this improved method is suitable and effective. It could detect the moving object area precisely.
提出了一种改进的基于时间差分的运动检测方法。该方法可以解决时间差分法在运动目标区域产生孔洞的普遍问题。首先,从图像序列中连续的两帧灰度帧计算出绝对差分图像;其次,对绝对差分图像进行低通滤波,转换成二值图像;第三,利用图像序列中的一些灰度图像计算出若干个二值图像。最后,对上述二值图像的像素进行算术运算,提取运动目标区域。实验结果表明,这种改进方法是合适和有效的。它可以精确地检测运动物体区域。
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引用次数: 14
Market Entry of Duopoly Wharf Enterprises at Container Port with Network Externality 网络外部性下集装箱港口双寡头码头企业的市场进入
Pub Date : 2009-05-23 DOI: 10.1109/IWISA.2009.5072948
Yuli Tian, S. He, Guiming Huang
This article in view of Sinotrans Guangdong LTD in face of whether enters Guangzhou Huangpu new port and what policy-making questions it will meet, through constructing Cournot model and Stackelberg model under network externalities, generally study on container port duopoly wharf enterprises' market entry's questions. The findings indicate that, through affecting the wharf enterprise's market share and the service price, network externalities finally affect wharf enterprise's profit; the classical duopoly game's first-mover advantage appears only when network externalities are quite weak. However, under the different market mode of entry, the bilateral market share and the price are not only decided by the strength of self-network externalities, but also decided by competitors' strength of network externalities.
本文针对中外运广东有限公司面对是否进入广州黄埔新港以及将会遇到哪些决策问题,通过构建网络外部性下的古诺模型和斯塔克尔伯格模型,对集装箱港口双寡头码头企业的市场进入问题进行了一般性的研究。研究结果表明,网络外部性通过影响码头企业的市场份额和服务价格,最终影响码头企业的利润;经典双寡头博弈的先发优势只有在网络外部性相当弱的情况下才会出现。然而,在不同的市场进入方式下,双边市场份额和价格不仅由自身网络外部性的强弱决定,也由竞争对手网络外部性的强弱决定。
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引用次数: 0
An Evolutionary ANN Based on Rough Set and Its Application in Power Grid Fault Diagnosis 基于粗糙集的进化神经网络及其在电网故障诊断中的应用
Pub Date : 2009-05-23 DOI: 10.1109/IWISA.2009.5072712
Sheng Lin, Zhengyou He, Yangfan Zhang, Q. Qian
In order to overcome the inherent flaws of artificial neural networks (ANN), such as long training time, slow convergence and low diagnosis accuracy, a novel evolutionary ANN combining with rough set (RS), named as RSANN, is suggested, and it's proposed to apply in power grid fault diagnosis. The ANN used is a three-layer back-propagation (BP) neural network. RS can reduce the dimensionality of attributes and find out the core attributes through its reduct. The attribute in this research is the information of circuit breakers (CBs) tripping and protection relays action, which is used to diagnose power grid fault. In RSANN, the RS is applied to serve for pretreatment unit which can deal with uncertain or incomplete information, and the core attributes are applied to optimize both topology and connection weights of ANN so as to simplify network structure and improve learning quality. Therefore, the disadvantages such as the incompleteness or error of ANN input data are resolved well through RSANN, and it has rapid reasoning, powerful error tolerance ability. In the end, the simulation experiment in power grid fault diagnosis shows the availability and accuracy of this method.
为了克服人工神经网络(ANN)固有的训练时间长、收敛速度慢、诊断准确率低等缺陷,提出了一种结合粗糙集(RS)的进化神经网络(RSANN),并将其应用于电网故障诊断。使用的人工神经网络是一个三层反向传播(BP)神经网络。RS可以将属性降维,通过降维找到核心属性。本研究的属性是断路器跳闸和保护继电器动作的信息,用于电网故障诊断。在RSANN中,利用RS作为处理不确定或不完全信息的预处理单元,利用核心属性对神经网络的拓扑和连接权进行优化,从而简化网络结构,提高学习质量。因此,通过RSANN很好地解决了人工神经网络输入数据的不完整或错误等缺点,并且具有推理速度快、容错能力强等特点。最后,通过对电网故障诊断的仿真实验,验证了该方法的有效性和准确性。
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引用次数: 1
Evaluation on Performance of the Tertiary Industry of Lucheng District in Wenzhou: A DEA Application 温州市鹿城区第三产业绩效评价:DEA应用
Pub Date : 2009-05-23 DOI: 10.1109/IWISA.2009.5072857
Ying Zhang, Weilai Huang, Jing Hu
Data Envelopment Analysis (DEA) is a non-parametric technique for measuring and evaluating the relative efficiencies of a set of decision-making units in terms of a set of common inputs and outputs, which is more popular in analyses of the emerging industry. With DEA, we handle multiple inputs and multiple outputs in Lucheng District of Wenzhou city, assess potential technical efficiency and scale efficient of its tertiary industry, find out some existent problems, and illuminate the route of development for Lucheng District in the future.
数据包络分析(Data Envelopment Analysis, DEA)是一种非参数分析方法,用于衡量和评估一组决策单元在一组共同投入和产出方面的相对效率,在新兴产业分析中更为流行。运用DEA对温州市鹿城区的多投入多产出进行分析,评估其第三产业潜在的技术效率和规模效率,找出存在的问题,为鹿城区未来的发展路径指明方向。
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引用次数: 0
Solve Zero-One Knapsack Problem by Greedy Genetic Algorithm 用贪心遗传算法求解0 - 1背包问题
Pub Date : 2009-05-23 DOI: 10.1109/IWISA.2009.5073116
Yuxiang Shao, Hongwen Xu, Weiming Yin
In order to overcome the disadvantages of the traditional genetic algorithm and improve the speed and precision of the algorithm, the author improved the selection strategy, integrated the greedy algorithm with the genetic algorithm and formed the greedy genetic algorithm. The paper discussed the basic idea and method to solve the zero-one knapsack problem using this greedy genetic algorithm. The experiments prove the feasibility and validity of the algorithm.
为了克服传统遗传算法的缺点,提高算法的速度和精度,作者改进了选择策略,将贪婪算法与遗传算法相结合,形成了贪婪遗传算法。本文讨论了利用贪心遗传算法求解0 - 1背包问题的基本思想和方法。实验证明了该算法的可行性和有效性。
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引用次数: 10
Real-Time Control of Autonomous Underwater Vehicles Based on Fuzzy Neural Network 基于模糊神经网络的自主水下航行器实时控制
Pub Date : 2009-05-23 DOI: 10.1109/IWISA.2009.5073026
F. Wang, Yuru Xu, Lei Wan, Ye Li
A real-time control scheme based on fuzzy neural network (FNN) is proposed for the motion control of autonomous underwater vehicles (AUVs) in this paper, for which the dynamics of the controlled system need not be completely known. A real-time desired state planning (DSP) based a sigmoid reference model is introduced to assist the FNN to keep the track error in a low level, and that also can serve as teaching signal to guide the training of the network, which makes it possible to implement the real-time motion control with FNN. The designed multilayered neural network architecture involves a modified error back propagation (EBP) as the learning algorithm, which is implemented by using the error at the output of the vehicle instead of that of the network so that the weights can be effectively adjusted to maximally decrease the system error. Results of simulation studies on the "AUV-XX" simulation platform are performed to illustrate the effectiveness of the presented scheme.
本文提出了一种基于模糊神经网络(FNN)的自主水下航行器运动控制的实时控制方案,该方案不需要完全知道被控系统的动力学特性。引入基于s型参考模型的实时期望状态规划(DSP),帮助FNN将跟踪误差保持在较低的水平,并可作为指导网络训练的教学信号,使FNN实现实时运动控制成为可能。设计的多层神经网络结构采用改进的误差反向传播(EBP)作为学习算法,利用车辆输出处的误差而不是网络输出处的误差来实现,从而可以有效地调整权值,最大限度地减小系统误差。在“AUV-XX”仿真平台上进行了仿真研究,验证了该方案的有效性。
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引用次数: 1
期刊
2009 International Workshop on Intelligent Systems and Applications
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