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2009 International Workshop on Intelligent Systems and Applications最新文献

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Rough Sets Based Hybrid Intelligent Fault Diagnosis for Precision Test Turntable 基于粗糙集的精密试验转台混合智能故障诊断
Pub Date : 2009-05-23 DOI: 10.1109/IWISA.2009.5073104
Baiting Zhao, Xijun Chen, Qingshuang Zeng
This paper is concerned with fault diagnosis for the precision test turntable (PTT). Using rough set theory combine with neural network, a forward greedy reduce algorithm based on rough set is presented to pre-process the raw fault information. By calculating the dependence and significance of the condition, the core attributes are gained and finally the reduction of the raw fault information is obtained. The worst case of computational complexity of reduction and the total computational times of the algorithm are presented. The reduced decision table will be used by the neural network as the training samples. Rough set method can effectively decrease the dimension of the information space. In this algorithm, the training samples for the neural network can be reduced dramatically, and the training time of the network is decreased. The method can detect the composed faults while keeping good robustness, and can reduce the false alarm rate and the missing alarm rate of the fault diagnosis system effectively.
本文对精密试验转台的故障诊断进行了研究。将粗糙集理论与神经网络相结合,提出了一种基于粗糙集的前向贪婪约简算法对原始故障信息进行预处理。通过计算条件的依赖度和重要度,得到核心属性,最终得到原始故障信息的约简。给出了最坏情况下的约简计算复杂度和算法的总计算次数。神经网络将使用约简后的决策表作为训练样本。粗糙集方法可以有效地降低信息空间的维数。该算法可以显著减少神经网络的训练样本,减少网络的训练时间。该方法能在保持良好鲁棒性的同时检测出组合故障,有效地降低了故障诊断系统的虚警率和漏警率。
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引用次数: 2
Classification of Remote Sensing Agricultural Image by Using Artificial Neural Network 基于人工神经网络的遥感农业影像分类
Pub Date : 2009-05-23 DOI: 10.1109/IWISA.2009.5072778
Haihui Wang, Junhua Zhang, K. Xiang, Liu Yang
A classification of remote sensing data by using several classifiers and neural networks is presented in this paper. The application was conducted using a scene about agricultural areas, and it contains several agricultural classes. Several classification methods were compared and tested over a multispectral scene containing agricultural classes using a data base, and the Hybrid Learning Vector Quantization neural network approaches are used to classify multispectral TM images. The main result obtained in this paper is that the neural network considered here provides a satisfying effect for the classification of agricultural multispectral images, and it means that this neural network architecture may be considered as a good alternative to the classical Bayesian method, especially when processing hyper-spectral data where several hundreds of spectral bands have to be considered together.
提出了一种基于分类器和神经网络的遥感数据分类方法。该应用程序是在一个农业区场景中进行的,它包含几个农业类。在一个包含农业类的多光谱场景中,对几种分类方法进行了比较和测试,并采用混合学习向量量化神经网络方法对多光谱TM图像进行分类。本文的主要结果是本文所考虑的神经网络对农业多光谱图像的分类提供了令人满意的效果,这意味着该神经网络架构可以被认为是经典贝叶斯方法的一个很好的替代方案,特别是在处理需要同时考虑数百个光谱波段的高光谱数据时。
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引用次数: 9
Development of Automatic Visual Inspection Sensor in Robotic Tailored Blank Welding 机器人定制毛坯焊接中自动视觉检测传感器的研制
Pub Date : 2009-05-23 DOI: 10.1109/IWISA.2009.5072831
Lei Zhang, Yongliang Xie
This paper describes the development of a vision inspection sensor system for the automation of laser welding processes in heavy industries. The system consists of PC based vision camera and stripe type laser diode. Its structure, basic principle of this system and the mathematic model and error analysis are also deascribed. A mathematic model is established in order to analyse the influence on sensor error from the geometric parameters. The simulation results are shown the relationship between error and coordinate of image points. Finally, the experiments results illustrate the mismatch size, weld slope, convexity , concavity, overthickness. Undercut and the bead width of the weld for the butt joint. And the feasibility and effectiveness of automatic visual inspection sensor are proved.
本文介绍了一种用于重工业激光焊接自动化的视觉检测传感器系统的研制。该系统由基于PC机的视觉摄像头和条纹型激光二极管组成。阐述了该系统的结构、基本原理、数学模型和误差分析。为了分析几何参数对传感器误差的影响,建立了数学模型。仿真结果显示了误差与图像点坐标之间的关系。最后,实验结果说明了错配尺寸、焊缝斜率、凸度、凹度、过厚。凹边和对接焊缝的焊头宽度。验证了自动视觉检测传感器的可行性和有效性。
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引用次数: 5
Research on Application of 1-Wire Bus Technology in Long Distance and Multi-Spot Temperature Monitoring 1线总线技术在远距离多点温度监测中的应用研究
Pub Date : 2009-05-23 DOI: 10.1109/IWISA.2009.5073056
Hongmei Xue
According to the request of the application environment of long distance and multi-spot temperature system, the author proposes the method of forceful actuation temperature monitoring about the 1-wire bus's field. By designing one driving circuit with proper rate of drop-down and drop-up, the driving force of the temperature monitoring can be enhanced greatly so as to support the multi-spot temperature monitoring in a longer distance, a bigger space and simultaneously realize the separation between the monitoring pattern and the searching pattern. In this way, we can avoid the occurrence of monitoring chaotic situations because of the lose of sensors thus guarantee the monitoring network's reliability, stability and intelligence, enabling the 1- wire bus monitor to be applied in a bigger scope.
根据远距离多点温度系统的应用环境要求,提出了一种针对一线总线现场的强制驱动温度监测方法。通过设计一个合适的下拉和上拉速率的驱动电路,可以大大增强温度监测的驱动力,从而支持更远距离、更大空间的多点温度监测,同时实现监测模式与搜索模式的分离。这样可以避免由于传感器丢失而出现监控混乱的情况,从而保证了监控网络的可靠性、稳定性和智能化,使1线总线监控能够得到更大的应用范围。
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引用次数: 0
Wind Turbine Control Strategy at Lower Wind Velocity Based on Neural Network PID Control 基于神经网络PID控制的低风速风力机控制策略
Pub Date : 2009-05-23 DOI: 10.1109/IWISA.2009.5073239
Xing-jia Yao, Xian-bin Su, L. Tian
For the variable speed operation of large scale wind turbine, the vibrations become key problem that can not be ignored. In this paper, the active vibration control based on Neural Network PID control strategy was researched. Firstly, PID control algorithm was analyzed. Then, the PID control based on Neural Network was described especially BP Network and its algorithm. In the end, this control method was verified using simulation and prototype test. Keywords-Control; PID; Neural Network; Bladed I.INTRODUCTION The more complicated of controlled system, the higher of people requirements, further, people need control system could adapt to uncertainty, time-varying objects and environment ability. Traditional control method based on exact model can hardly meet the requirements. Control is defined as concept including decision, planning and learning ability. The neural network is paid more and more attention because of these advantages mentioned above. The control diagram of wind turbine is shown in Figure 1.
对于大型风力发电机组的变速运行,振动问题成为不可忽视的关键问题。本文研究了基于神经网络PID控制的振动主动控制策略。首先,分析了PID控制算法。然后介绍了基于神经网络的PID控制,特别是BP网络及其算法。最后,通过仿真和样机试验对该控制方法进行了验证。Keywords-Control;PID;神经网络;被控系统越复杂,人们的要求也就越高,进一步要求控制系统具有适应不确定性、时变对象和环境的能力。传统的基于精确模型的控制方法很难满足要求。控制是一个包含决策、计划和学习能力的概念。由于这些优点,神经网络越来越受到人们的重视。风力机控制图如图1所示。
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引用次数: 15
Image Segmentation Algorithm of Variable Precision Based on Granular Matrix Model 基于颗粒矩阵模型的变精度图像分割算法
Pub Date : 2009-05-23 DOI: 10.1109/IWISA.2009.5072901
Xiaoli Hao, R. Lin, Fu Duan
In order to deal with space correlation of image information, a new image segmentation algorithm based on granular matrix model is proposed. Firstly, we define granular matrix model, which is used to build knowledge granular of an image. Secondly, we introduce classifying error precision to the model, and construct granular layers of an image by it. Thirdly, for the need of segmentation precision, we choose unit granular layer and realize reduction by granular matrix. Finally, implementing the combination of the similar regions and the image segmentation is accomplished. In order to certify the new algorithm, it is applied to image segmentation tests. The results indicate that it is more suitable for actual need, which not only reduce complexity of space and time, but also provide new thoughts in image process. Keywords-image segmentation; granular computing; variable precision
为了处理图像信息的空间相关性,提出了一种基于颗粒矩阵模型的图像分割算法。首先,我们定义了颗粒矩阵模型,该模型用于构建图像的知识颗粒。其次,在模型中引入分类误差精度,利用该模型构建图像的颗粒层;第三,基于分割精度的需要,选择单位颗粒层,通过颗粒矩阵实现约简。最后,实现了相似区域的结合和图像分割。为了验证新算法的有效性,将其应用于图像分割测试。结果表明,该方法更符合实际需要,不仅降低了空间和时间的复杂性,而且为图像处理提供了新的思路。Keywords-image分割;细粒度的计算;可变精度
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引用次数: 0
Restudying the Artificial Immune Model for Network Intrusion Detection 网络入侵检测人工免疫模型再研究
Pub Date : 2009-05-23 DOI: 10.1109/IWISA.2009.5073094
Xianjin Fang, Jingzhao Li, Longshu Li
In order to quicken the affinity maturation process of detector population and improve the efficiency of network intrusion detection, this paper describes detailed vaccine operator, algorithm of adaptive extracting vaccine and Immune Evolutionary Algorithm (IEA), and then design a novel artificial immune model and algorithm for network intrusion detection which integrates Negative Selection Algorithm (NSA) with IEA. This model can also satisfy three requirements of distributed, self-organizing and lightweight. The network intrusion detection experiments based on the novel model and algorithm are designed to compare with Kim’s artificial immune model for network intrusion detection which is based on Clonal Selection Algorithm (CSA) and NSA. Experimental results show that the novel model and its algorithm quickens the affinity maturation process of detector population and stably increases the detection rate along with increasing evolutionary generation; but in Kim’s conceptual mode, the affinity maturation process of detector population takes more time, the detection rate falls into a little degradation and maintains invariant for a long time.
为了加快探测器种群亲和成熟过程,提高网络入侵检测效率,详细介绍了疫苗算子、自适应提取疫苗算法和免疫进化算法,设计了一种将负选择算法与免疫进化算法相结合的网络入侵检测人工免疫模型和算法。该模型还能满足分布式、自组织和轻量化三个要求。设计了基于该模型和算法的网络入侵检测实验,并与Kim基于克隆选择算法(CSA)和NSA的网络入侵检测人工免疫模型进行了比较。实验结果表明,该模型及其算法加快了检测种群的亲和成熟过程,随着进化代数的增加,检测率稳定提高;但在Kim的概念模型中,检测器种群的亲和成熟过程需要更长的时间,检出率陷入轻微的下降并长期保持不变。
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引用次数: 3
An On-Line Arterial Route Travel Time Prediction Application Using ANFIS 基于ANFIS的动脉行程时间在线预测应用
Pub Date : 2009-05-23 DOI: 10.1109/IWISA.2009.5072727
Miao Zhang
Travel time study is basis to other traffic information service. Lots of factors like the intersection delay, the interference of non-motor vehicles and pedestrians affect the urban arterial traffic flow, making it displays much more complicated characteristics than the one of freeway. There are lots of efforts towards urban arterial route travel time forecasting methods; in this study, an ANFIS (Adaptive Neuro-Fuzzy Inference System) based real-time arterial route travel time prediction method is proposed, and tested using field data on arterial route segments in Shanghai, which covers both normal and failure conditions of detectors. Experiment results were then evaluated by a set of criteria. Results show that this approach has very good performance if being well trained with a large amount of data, even encountering incomplete information (detector failure), which validates the promising accuracy and robust of this approach. A sensitivity analysis of model inputs then carried out. Because the training procedure is usually costly, the direct citywide implantation of this approach might not be feasible; however, with necessary improvement of training strategy, the proposed approach shall be even more satisfying. Keywords-ANFIS, Travel Time, Arterial Route
出行时间研究是提供其他交通信息服务的基础。交叉口延迟、非机动车和行人的干扰等诸多因素影响着城市主干道交通流,使其表现出比高速公路复杂得多的特征。城市主干道行车时间预测方法的研究有很多;本文提出了一种基于自适应神经模糊推理系统(ANFIS)的动脉路线行驶时间实时预测方法,并利用上海主干道路段的现场数据进行了测试,该方法涵盖了检测器正常和故障情况。然后用一套标准对实验结果进行评价。结果表明,在大量数据的训练下,即使遇到不完全信息(检测器失效),该方法也具有很好的性能,验证了该方法具有良好的准确性和鲁棒性。然后对模型输入进行敏感性分析。由于培训程序通常很昂贵,在全市范围内直接实施这种方法可能不可行;但是,如果对培训策略进行必要的改进,所提出的方法将更加令人满意。关键词:anfis,出行时间,主干道
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引用次数: 0
Study on Optimal Delivery Strategy Based on the Third-Party Storage Cost 基于第三方仓储成本的最优配送策略研究
Pub Date : 2009-05-23 DOI: 10.1109/IWISA.2009.5073138
Zhengchi Liu, M. Lai
Based on the financing system among upstream supplier enterprises, third-party financing warehouses, manufacturers and banks, a model is established respectively for the minimum production cost or the maximum loan amount. Further analysis is made towards the impact of the storage cost parameter to the delivery strategies for suppliers, which provides recommendations for suppliers to choose the best delivery strategy to achieve maximum utility.
以上游供应商企业、第三方融资仓库、制造商和银行之间的融资体系为基础,分别建立了生产成本最小和贷款金额最大的融资模型。进一步分析了仓储成本参数对供应商配送策略的影响,为供应商选择最佳配送策略提供建议,以实现最大的效用。
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引用次数: 0
Risk Assessment of International Project Contracting Based on Unascertained Set 基于未确知集的国际工程承包风险评估
Pub Date : 2009-05-23 DOI: 10.1109/IWISA.2009.5073098
Shujing Zhou, Li Liu, Chao Wu, Yancang Li
To management the risk of International Project Contracting where the chance and risk are accreted and the risk is bigger than the domestic engineering, the paper sets up the comprehensive evaluation system and a model of risk assessment by using the unascertained set for evaluating the risk of the international project contracting. Finally, the practicality and feasibility of the model are illustrated by the engineering practice.
针对国际工程承包机会和风险都较大且风险大于国内工程的风险管理问题,本文建立了综合评价体系和未确知集风险评价模型,对国际工程承包风险进行了评价。最后,通过工程实践验证了该模型的实用性和可行性。
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引用次数: 0
期刊
2009 International Workshop on Intelligent Systems and Applications
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