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Genetic Fuzzy + PI Path Tracking Control of a Nonholonomic Mobile Robot

电子学报(英文版) 2011年第1期20卷 31-34页

作者： CAO Zhengcai ZHAO Yingtao WU Qidi College of Information Science and Technology Beijing University of Chemical Technology Beijing China The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China

A mobile robot is one of the well-known nonholonomic systems. The genetic fuzzy + PI path track- ing control applied to a mobile robot is presented. The pro- posed controller composes of two fuzzy + PI controllers which are employed to control the angular velocity to- gether, and one fuzzy + PI controller that is utilized to adjust the speed of mobile robot solely. Moreover, the fuzzy controller is designed to track reference path in ap- proaching phase and PI controller is operated to diminish the tracking error in stable phase. In order to obtain bet- ter tracking performance, Genetic algorithm (GA) is used to optimize controller parameters. Finally, computer sim- ulation results are given to illustrate the effectiveness of the proposed control scheme.

关键词：模糊PI控制器移动机器人机器人控制非完整系统路径跟踪遗传算法模糊控制器控制器参数

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Network Security Situation Evaluation Based on Modified D-S Evidence Theory

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Wuhan University Journal of Natural Sciences 2014年第5期19卷 409-416页

作者： WANG Chundong ZHANG Yukey Laboratory of Computer Vision and System Ministry of Education/Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology

With the rapid development of global information and the increasing dependence on network for people, network security problems are becoming more and more serious. By analyzing the existing security assessment methods, we propose a network security situation evaluation system based on modified D-S evidence theory is proposed. Firstly, we give a modified D-S evidence theory to improve the reliability and rationality of the fusion result and apply the theory to correlation analysis. Secondly, the attack successful support is accurately calculated by matching internal factors with external threats. Multi-module evaluation is established to comprehensively evaluate the situation of network security. Finally we use an example of actual network datasets to validate the network security situation evaluation system. The simulation result shows that the system can not only reduce the rate of false positives and false alarms, but also effectively help analysts comprehensively to understand the situation of network security.

关键词： network security situation evaluation informationfusion D-S evidence theory Bayes network theory

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Semi-probabilistic routing in intermittently connected mobile ad hoc networks

Semi-probabilistic routing in intermittently connected mobil...

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2007 2nd International Conference on Communications and Networking in China, ChinaCom 2007

作者： Ke, Shi Laboratory of Services Computing Technology and System College of Computer Science and Technology Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781424410095

ICMANs (Intermittently Connected Mobile Ad hoc Networks) are wireless networks where most of the time there does not exist a complete path from the source to the destination. In this paper, a novel routing approach, SPR (Semi-Probabilistic Routing), is proposed to address routing problem in ICMANs. SPR takes into account information about host mobility and connectivity changes to produce estimates enabling more accurate message forwarding. These include maintaining proactive routing zones for stable local topology to minimize blind message forwarding, and identifying potential carriers to maximize message delivery despite network partitions and intermittent connectivity. We compare the performance of our protocol against others, using a mobility model validated with real-world traces.

关键词： Ad hoc networks

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A novel snowdrift game model with edge weighting mechanism on the square lattice

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Frontiers of physics 2012年第3期7卷 366-372页

作者： Juan-uan Zhang Hong-yun Ning Zi-yu Yin Shi-wen Sun Li Wang Jun-qing Sun Cheng-yi Xia Tianjin Key Laboratory of Intelligence Computing and Novel Softwave Technology Tianjin University of Technology Tianjin 300384China Key Laboratory of Computer Vision and System of Ministry of Education Tianjin University of TechnologyTianjin 300384China School of Physics Nankai UniversityTianjin 300071China

We propose a novel snowdrift game model with edge weighting mechanism to explore the cooperative behaviors among the players on the square lattice. Based on the assumption of three types of weight distribution including uniform, exponential and power-law schemes, the cooperation level is largely boosted in contrast with the traditional snowdrift game on the unweighted square lattice. Exten- sive numerical simulations indicate that the fraction of cooperators greatly augments, especially for the intermediate range of cost-to-benefit ratio r. Furthermore, we investigate how the cooperative behaviors are affected by the undulation amplitude of weight distribution and noise strength of strat- egy selection, respectively. The simulation results will be conducive to further understanding and analyzing the emergence of cooperation, which is a ubiquitous phenomenon in social and biological science.

关键词： snowdrift game edge weighting mechanism cooperative dynamics

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New explicit multi-symplectic scheme for nonlinear wave equation

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Applied Mathematics and Mechanics(English Edition) 2014年第3期35卷 369-380页

作者：李昊辰孙建强秦孟兆 Department of Mathematics College of Information Science and TechnologyHainan University State Key Laboratory of Scientific and Engineering Computing Academy of Mathematics and System SciencesChinese Academy of Sciences

Based on splitting multi-symplectic structures, a new multi-symplectic scheme is proposed and applied to a nonlinear wave equation. The explicit multi-symplectic scheme of the nonlinear wave equation is obtained, and the corresponding multi-symplectic conservation property is proved. The backward error analysis shows that the explicit multi-symplectic scheme has good accuracy. The sine-Gordon equation and the Klein-Gordon equation are simulated by an explicit multi-symplectic scheme. The numerical results show that the new explicit multi-symplectic scheme can well simulate the solitary wave behaviors of the nonlinear wave equation and approximately preserve the relative energy error of the equation.

关键词： nonlinear wave equation multi-symplectic method backward error analysis

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Will the fibers of the future be considered fibers?

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National Science Review 2024年第10期11卷 15-17页

作者： Dewen Xu Ya Liu Hailiang Wang Wei Yan Changjun Jiang Meifang Zhu State Key Laboratory for Modification of Chemical Fibers and Polymer Materials College of Materials Science and Engineering Donghua University Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Department of Computer Science and Technology Tongji University

Fiber materials are key materials that have changed human history and promoted the progress of human civilization. In ancient times, humans used feathers and animal skins for clothing, and later they widely employed natural fibers such as cotton, hemp, silk and wool to make fabrics(Fig. 1a). Chinese ancestors had mastered the art of natural fiber weaving as early as the Neolithic *** thousand years ago, people were already familiar with and adept at techniques for spinning natural fibers [1].

关键词： future will considered fibers

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Light field imaging based on a parallel SVM method for recognizing 2D fake pedestrians

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Optoelectronics Letters 2022年第1期18卷 48-53页

作者： JIA Chen ZHANG Yao SHI Fan ZHAO Meng Key Laboratory of Computer Vision and System of Ministry of Education Tianjin Key Laboratory of Intelligence Computing and Novel Software TechnologyTianjin University of TechnologyTianjin 300384China The MOE Key Laboratory of Weak-Light Nonlinear Photonics Nankai UniversityTianjin 300457China

It is novel to apply three-dimensional(3D)light field imaging technology to recognize two-dimensional(2D)fake *** this paper,we propose a parallel support vector machine(SVM)method based on 3D light field imaging(light field camera)and machine learning techniques.A light field(LF)camera with robust sensors,which is able to record rich 3D information,is used as hardware *** of oriented gradient(HOG)feature extraction algorithm and SVM classification method are used to recognize the real and 2D fake pedestrians ***,we carry out an experiment on our improved LF pedestrian *** experimental results of parameter optimization study show that in the case of 400 training samples(200 positive samples and 200 negative samples),120 to 420 testing samples,and an HOG cellsize as 8×8,the best recognition accuracy with polynomial kernel function is improved by more than 2%compared with the previous *** best accuracy is 99.17%.Otherwise,the recognition accuracy of more than 98.00%will be obtained even under other experimental conditions.

关键词： hardware field method

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Multiscale modeling for classification of SAR imagery using hybrid EM algorithm and genetic algorithm

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Progress in Natural Science:Materials International 2009年第8期19卷 1033-1036页

作者： Xianbin Wen a,b, Hua Zhang a,b, Jianguang Zhang a,b, Xu Jiao a,b, Lei Wang a,b a Tianjin key laboratory of Intelligence computing and Novel Software technology, Tianjin University of technology, Tianjin 300191, China b key laboratory of Computer Vision and system (Tianjin University of technology), Ministry of Education, Tianjin 300191, China [a]Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology Tianjin 300191 China [b]Key Laboratory of Computer Vision and System (Tianjin University of Technology) Ministry of Education Tianjin 300191 China

A novel method that hybridizes genetic algorithm (GA) and expectation maximization (EM) algorithm for the classification of synthetic aperture radar (SAR) imagery is proposed by the finite Gaussian mixtures model (GMM) and multiscale autoregressive (MAR) model. This algorithm is capable of improving the global optimality and consistency of the classification performance. The experiments on the SAR images show that the proposed algorithm outperforms the standard EM method significantly in classification accuracy.

关键词： SAR imagery Classification Multiscale Hybrid EM algorithm Genetic algorithm

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A Reduced Reachability Tree for a Class of Unbounded Petri Nets

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IEEE/CAA Journal of Automatica Sinica 2015年第4期2卷 345-352页

作者： Shouguang Wang Mengdi Gan Mengchu Zhou Dan You School of Information and Electronic Engineering Zhejiang Gongshang University State Key Laboratory for Manufacturing Systems Engineering Xi’an Jiaotong University Ministry of Education(MoE)Key Laboratory of Embedded System and Service Computing Tongji University MoE Key Laboratory of Embedded System and Service Computing Tongji University Department of Electrical and Computer Engineering New Jersey Institute of Technology

As a powerful analysis tool of Petri nets, reachability trees are fundamental for systematically investigating many characteristics such as boundedness, liveness and reversibility. This work proposes a method to generate a reachability tree, called ωRT for short, for a class of unbounded generalized nets called ω-independent nets based on new modified reachability trees (NMRTs). ωRT can effectively decrease the number of nodes by removing duplicate and ω-duplicate nodes in the tree, and verify properties such as reachability, liveness and deadlocks. Two examples are provided to show its superiority over NMRTs in terms of tree size. © 2014 Chinese Association of Automation.

关键词： Petri nets

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DPNet: Dynamic Pooling Network for Accurate and Efficient Size-Aware Tiny Object Detection

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IEEE Internet of Things Journal 2025年

作者： Gong, Luqi Chen, Haotian Chen, Yikun Yao, Tianliang Li, Chao Zhao, Shuai Han, Guangjie Beijing University of Posts and Telecommunications School of Computer Science Beijing China Zhejiang Lab Research Center for Space Computing System Hangzhou China Southwest Jiaotong University SWJTU-LEEDS Joint School Chengdu China LTD Guangdong Zhiyun City construction Technology Co Zhuhai China Tongji University College of Electronic and Information Engineering Department of Control Science and Engineering Shanghai China Hohai University Key Laboratory of Maritime Intelligent Network Information Technology Ministry of Education China

In unmanned aerial systems, especially in complex environments, accurately detecting tiny objects is crucial. Resizing images is a common strategy to improve detection accuracy, particularly for small objects. However, simply enlarging images significantly increases computational costs and the number of negative samples, severely degrading detection performance and limiting its applicability. This paper proposes a Dynamic Pooling Network (DPNet) for tiny object detection to mitigate these issues. DPNet employs a flexible down-sampling strategy by introducing a factor (df) to relax the fixed down-sampling process of the feature map to an adjustable one. Furthermore, we design a lightweight predictor to predict df for each input image, which will be used to decrease the resolution of feature map in backbone. Thus, we achieve input-aware down-sampling. We design an Adaptive Normalization Module (ANM) to make a unified detector well compatible with different dfs. At the same time, we also design a guidance loss to supervise the predictor’s training. DPNet realizes the dynamic allocation of computing resources to trade off detection accuracy and efficiency through this. Experiments on the TinyCOCO and TinyPerson datasets show that our DPNet can save over 35% and 25% GFLOPs, respectively, while maintaining comparable detection *** code will be made publicly available. © 2014 IEEE.

关键词： Object detection

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