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Advances in intelligent Systems and Computing 2018年 650卷 299-311页

作者： Wang, Shuru Cao, Donglin Lin, Dazhen Chao, Fei Cognitive Science Department Xiamen University Xiamen China Fujian Key Laboratory of Brain-Inspired Computing Technique and Applications Xiamen University Xiamen China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou China

ISBN: (纸本)9783319669380

Analysis of traffic condition is of great significance to urban planning and public administration. However, traditional traffic condition analysis approaches mainly rely on sensors, which are high-cost and limit their coverage. To solve these problems, we propose a semi-supervised learning method which uses the social network data instead and analyzes the traffic condition based on user’s emotion tendency. First we train the Gated Recurrent Unit (GRU) model to estimate the sentiment of microblog with traffic information, then using the emotional tendency to predict whether traffic jams happen or not. In order to reduce the data annotated by manpower, we propose a new idea to employ the Conditional Generative Adversarial Networks (CGAN) to generate samples which are as a supplement to the training set of GRU. Finally compared with the GRU model trained by solely the manual annotation data, our method improves the classification accuracy by 4.07%. We also use our model to predict the time and roads of traffic jams in 4 Chinese cities which is proved to be effective. © 2018, Springer International Publishing AG.

关键词： Generative adversarial networks

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Sentiment Analysis Model Based on Structure Attention Mechanism

Advances in Intelligent Systems and Computing

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Advances in intelligent Systems and Computing 2018年 650卷 17-27页

作者： Lin, Kai Lin, Dazhen Cao, Donglin Cognitive Science Department Xiamen University Xiamen China Fujian Key Laboratory of Brain-Inspired Computing Technique and Applications Xiamen University Xiamen China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou China

ISBN: (纸本)9783319669380

Since the long short-term memory (LSTM) network is a sequential structure, it is difficult to effectively represent the structural level information of the context. Sentiment analysis based on the original LSTM causes a problem of structural level information loss, and its capacity to capture the context information is finite. To address this problem, we proposed a novel structure-attention-based LSTM as a hierarchical structure model. It may capture relevant information in the context as much as possible. We propose HM (ht matrix) to storage the structural information of the context. Furthermore, we introduce the attention mechanism to realize vector selection. Compared with the original LSTM and normal attention-based sentiment classification methods, our model obtains a higher classification precision. It is proved that the structure-attention-based method proposed in this study has an advantage in capturing the potential semantic structure. © 2018, Springer International Publishing AG.

关键词： Long short-term memory

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Optimal seam line detection in laplacian pyramid domain for image stitching

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Journal of Computers (Taiwan) 2018年第1期29卷 209-219页

作者： Yan, Wu-Xia Liu, Chuan-Cai Hu, Jun School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350121 China

Parallax handing is a challenging problem for image stitching. Optimal seam line method is employed in this paper to deal with the misalignment on panoramas caused by parallax problem. It's an important method for orthoimage stitching in remote sensing. However, failures occur when it used in common image stitching due to the parallax problem. In order to obtain a better panorama for common image, the proposed approach mainly employs optimal seam line and contains the following three steps. First, the parallax problem can be alleviated by geometric correction. Then, the optimal seam line is detected within the overlapping region by dynamic programming in Laplacian pyramid domain. And images were blended by using blending trick on each corresponding level of the pyramids. Finally, the convincing panorama can be obtained by reconstructing the panoramic pyramid. The experiments demonstrated that the proposed method can obtain the clear and seamless panoramas. © 2018 Computer Society of the Republic of China. All rights reserved.

关键词： Remote sensing

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Design and Implementation of Carrier Detection System Based on FPGA

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Journal of Physics: Conference Series 2020年第4期1624卷

作者： Xian Zhang Taiguo Qu Yiwen Liu Dong Yin Shaowei Deng School of Computer Science and Engineering Huaihua University Huaihua 418000 Hunan P. R. China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua 418000 Hunan P. R. China Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Huaihua 418000 Hunan P. R. China

In order to better monitor and manage the signal transmission in the communication system and base station, and carrier detection is more effective. This paper designs a carrier(Carrier frequency) detection system based on FPGA, including system design requirements, FPGA selection, system framework design, carrier detection method design and so on. The performance indexes of the system are tested, such as carrier frequency range, carrier search time, carrier detection number and CPU consumption rate. The system has the advantages of high flexibility and good portability, and has a good application prospect in communication system, base station and other equipment.

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Simple Iterative Clustering on Graphs for Robust Model Fitting

Simple Iterative Clustering on Graphs for Robust Model Fitti...

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IEEE Visual Communications and image processing (VCIP)

作者： Hailing Luo Guobao Xiao Hanzi Wang Fujian Key Laboratory of Sensing and Computing for Smart City School of Information Science and Engineering Xiamen University Xiamen China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou China

ISBN: (纸本)9781538644591;9781538644584

In this paper, we propose a novel method, simple iterative clustering on graphs (SICG), to deal with robust model fitting problems. Specifically, we first construct a graph, where each vertex denotes a model hypothesis and each edge represents the similarity between two model hypotheses, for model fitting. We then propose a simple iterative clustering algorithm, which adapts the k-medoids clustering algorithm, to intuitively estimate model instances in data. The proposed SICG method is able to effectively fit and segment multiple-structure data contaminated with a large number of outliers and noises. Experimental results show that SICG achieves superior fitting results over several state-of-the-art model fitting methods on real images.

关键词： Computational modeling Clustering algorithms Data models Iterative algorithms Adaptation models image segmentation Mathematical model

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A Geometric Approach to Second-Order Consensus of Heterogeneous Networked Systems

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IEEE Transactions on Cybernetics 2018年 2018 Jan 9页

作者： Su, Housheng Ye, Yanyan Chen, Xia He, Haibo School of Automation Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 China. China China Department of Electrical Computer and Biomedical Engineering University of Rhode Island Kingston RI 02881 USA. United States

This paper investigates second-order consensus of networked systems with heterogeneous intrinsic nonlinear dynamics via a geometrical method, in which the nonlinear dynamics are governed by both velocity and position. First, two necessary conditions are deduced for the existence of consensus solutions by analyzing the inherent nonlinear dynamics of isolated nodes. Then a closed invariant set is constructed via geometrical methods. The nonempty of the set implies the existence of consensus solution. Assuming that the primary and the second dimension about the above invariant set are the same linear subspace, the system can be divided into two simple subsystems through a linear transformation. In addition, some sufficient conditions are proposed for reaching the global consensus based on matrix theory and Lyapunov method. Finally, numerical simulation results are provided to illustrate the validity of theoretical analysis. IEEE

关键词： Multi agent systems

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Varying control intensity of synchronized chaotic system with time delay

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Journal of Physics: Conference Series 2021年第1期1828卷

作者： Babatunde O. Onasanya Shiping Wen Yuming Feng Wei Zhang Ning Tang Adeleke T. Ademola Key Laboratory of Intelligent Information Processing and Control Chongqing Three Gorges University Wanzhou Chongqing 404100 China Department of Mathematics University of Ibadan Ibadan Nigeria Australian AI Institute University of Technology Sydney Ultimo NSW 2007 Australia School of Computer Science and Engineering Chongqing Three Gorges University Wanzhou Chongqing 404100 China Chongqing Engineering Research Center of Internet of Things and Intelligent Control Technology Chongqing Three Gorges University Wanzhou Chongqing 404100 China School of Three Gorges Artificial Intelligence Chongqing Three Gorges University Wanzhou Chongqing 404100 China Department of Mathematics Obafemi Awolowo University Post Code 220005 Ile-Ife Nigeria

Hyperchaotic system is a very useful tool in secure and encrypted communications. But situations arise when engineers and scientists seek to synchronize two hyperchaotic systems. This gives another (error) system. The goal is to minimize the error as much as can be in order to make one system look like the other by synchronization. This is a particularly challenging situation. In this paper, two hyperchaotic systems are synchronized by impulsive control. Also, the condition for uniform asymptotic stability of the synchronized error system was given. Finally, the simulation results to justify the reliability of this method is also presented.

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Motion Blurred Star image Centroid Optimized Extraction Based on Prior Gaussian Distribution 29

Motion Blurred Star Image Centroid Optimized Extraction Base...

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第29届中国控制与决策会议

作者： Peng Dingbang Chen Hao Sang Xiaochong Li Jianxun School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Institute of Spaceflight Control Technology Shanghai Key Laboratory of Aerospace Intelligent Control Technology

ISBN: (纸本)9781509046584

Star centroid extraction is the precondition of star recognition in star navigation *** image will be motion blurred under high dynamic *** methods such as Wiener filter method,restore the blurred star image with an estimated PSF to calculate the star *** unique characteristic of star images different from general images is ignored in conventional *** addition,the error of motion blur parameters estimation and the approximate linear motion model can decrease the accuracy of star centroids *** paper proposes a method utilizing the prior Gaussian distribution information of star energy to deal with the motion blurred star *** experimental results demonstrate that the proposed method gets smaller error in star centroids calculation compared with the conventional estimation method.

关键词： Motion blur Star image restoration Centroid extraction Gaussian distribution Optimize

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Design of gear reducer based on FOA optimization algorithm 1st

Design of gear reducer based on FOA optimization algorithm

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1st International Conference on Smart Vehicular Technology, Transportation, Communication and Applications, VTCA 2017

作者： Lin, Xiaojia Zhang, Fuquan Xu, Lin Department of Computer Science Fujian Business University Fuzhou350012 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang Univeristy Fuzhou350121 China School of Software Beijing Institute of Technology Beijing100081 China Innovative Information Industry Research Institute Fujian Normal University Fuzhou350300 China

ISBN: (纸本)9783319707297

In order to optimize the design of gear reducer, gear reducer optimal design to improve reliability and security, slow convergence and local optimum for FOA algorithm is proposed based on the improved type FOA gear reducer optimization design model. To avoid falling into local optimum Drosophila optimization algorithms, improved FOA algorithm by introducing a correction factor. Superior to the gear reducer seven variables optimization design model for the study, to ensure the safety and reliability of the premise, the FOA has the advantage of improved convergence speed and avoid local optimization problems, in order to verify the proposed method and reliability. © Springer International Publishing AG 2018.

关键词： Reliability

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A bidirectional collaborative filtering recommender system based on EM algorithm 1st

A bidirectional collaborative filtering recommender system b...

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1st International Conference on Smart Vehicular Technology, Transportation, Communication and Applications, VTCA 2017

作者： Mao, Yu Zhang, Fuquan Xu, Lin Zhang, Dakui Yang, Hui School of Computer Science and Technology Beijing Institute of Technology Beijing China School of Software Beijing Institute of Technology Beijing100081 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350121 China Innovative Information Industry Research Institute Fujian Normal University Fuzhou350300 China

ISBN: (纸本)9783319707297

Collaborative filtering is a promising recommendation technique for predicting the preferences of users in recommender systems. The date coming from recommender system is not only big but also sparse. It motivates the need for a more intelligent approach to obtain the tastes of users. In this paper we present a novel bidirectional collaborative filtering method based on EM algorithm. We combine user rating with item rating to build a new rating matrix and calculate a steady result by iterating this strategy. The empirical evaluation demonstrates that our technique have encouraging result contrast to the traditional approaches. © Springer International Publishing AG 2018.

关键词： Collaborative filtering

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