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Swaying Tree Simulation by Slicing Partition

Chinese Journal of Electronics 2020年第5期29卷 826-832页

作者： TANG Jing WANG Yinghui WANG Ningna NING Xiaojuan LYU Ke SUI Liansheng SHI Zhenghao Faculty of Automation and Information Engineering Xi'an University of Technology School of Artificial Intelligence and Computer Science Jiangnan University The University of Texas at Dallas School of Engineering Sciences University of Chinese Academy of Sciences

The key of swaying tree simulation is to capture the essence of the interaction between wind and tree, which has not received much attention from scholars. In this paper, we present a method for simulating swaying tree based on slicing partition. The tree is divided into multiple "slices", and then jointly moved to simulate the tree swaying in wind. By slicing partition,the motion of any slice is independent of the others concurrently, which provides a parallel spatial topology for real-time calculation. Moreover, based on the fact that the wind will blow to a tree partly rather than the whole, partial swayings of the tree are also simulated. The experimental results show the correctness and effectiveness of our method.

关键词： Slicing Damping slicing partition geophysics computing swaying tree simulation Tree swaying wind vegetation

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Discovering admissible Web services with uncertain QoS

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Frontiers of computer science 2015年第2期9卷 265-279页

作者： Xiaodong FU Kun YUE Li LIU Ping ZOU Yong FENG Yunnan Provincial Key Laboratory of Computer Technology Application Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming 650500 China School of Information Science and Engineering Yunnan University Kunming 650091 China Faculty of Management and Economics Kunming University of Science and Technology Kunming 650093 China

Open and dynamic environments lead to inher- ent uncertainty of Web service QoS （Quality of Service）, and the QoS-aware service selection problem can be looked upon as a decision problem under uncertainty. We use an empiri- cal distribution function to describe the uncertainty of scores obtained from historical transactions. We then propose an approach to discovering the admissible set of services in- cluding alternative services that are not dominated by any other alternatives according to the expected utility criterion. Stochastic dominance （SD） rules are used to compare two services with uncertain scores regardless of the distribution form of their uncertain scores. By using the properties of SD rules, an algorithm is developed to reduce the number of SD tests, by which the admissible services can be reported pro- gressively. We prove that the proposed algorithm can be run on partitioned or incremental alternative services. Moreover, we achieve some useful theoretical conclusions for correct pruning of unnecessary calculations and comparisons in each SD test, by which the efficiency of the SD tests can be im- proved. We make a comprehensive experimental study using real datasets to evaluate the effectiveness, efficiency, and scal- ability of the proposed algorithm.

关键词： Web services uncertain QoS partial preference,empirical distribution function stochastic dominance admis-sible set

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An E-Commerce Recommender System Based on Click and Purchase Data to Items and Considered of Interest Shifting of Customers

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China Communications 2015年第S2期12卷 72-82页

作者： Duo Lin Wu Zhaoxia XU Shenggang School of Computer and Communication Engineering University of Science and Technology Beijing Faculty of Information Engineering and Automation Kunming University of Science and Technology School of Applied Mathematics Xinjiang University of Finance and Economics

A well-performed recommender system for an e-commerce web site can help customers easily find favorite items and then increase the turnover of merchants, hence it is important for both customers and merchants. In most of the existing recommender systems, only the purchase information is utilized data and the navigational and behavioral data are seldom concerned. In this paper, we design a novel recommender system for comprehensive online shopping sites. In the proposed recommender system, the navigational and behavioral data, such as access, click, read, and purchase information of a customer, are utilized to calculate the preference degree to each item; then items with larger preference degrees are recommended to the customer. The proposed method has several innovations and two of them are more remarkable: one is that nonexpendable items are distinguished from expendable ones and handled by a different way; another is that the interest shifting of customers are considered. Lastly, we structure an example to show the operation procedure and the performance of the proposed recommender system. The results show that the proposed recommender method with considering interest shifting is superior to Kim et al(2011) method and the method without considering interest shifting.

关键词： recommender system online shopping e-commerce preference degree

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Small-Signal and Transient Stability Investigation of Inverter Grid Synchronization 27

Small-Signal and Transient Stability Investigation of Invert...

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27th International Conference on Circuits, Systems, Communications and computers, CSCC 2023

作者： Scholey, Alexander Jeinsch, Torsten University of Rostock Institute of Automation Faculty of Computer Science and Electrical Engineering Germany

ISBN: (纸本)9798350337594

Grid synchronisation is essential for grid following inverter control. Typically, a phase-locked loop (PLL) is used to perform the synchronisation, but it is known that the PLL can fail to synchronise with the grid in weak grid scenarios. Although there have been many studies on this topic which relate the grid impedance, the grid voltage and the PLL parameterisation to the grid synchronisation, comprehensive analyses are difficult due to the nonlinear nature of the underlying system. Therefore, the exact relationships remain unclear. This paper investigates the stability of PLL-based grid synchronisation for a grid-side inverter with LC-type output filter and RL-type grid impedance. An analytical steady-state solution is presented, which is used for linearization and evaluation of the small-signal stability. Additionally, the transient stability with consideration of nonlinearities is investigated and a condition for stability of the PLL-based grid synchronization in the transient case is derived. The results are validated by numerical simulations. © 2023 IEEE.

关键词： Stability

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DFGCN: Decoupled dual-flow dynamic graph convolutional network for multivariate time series forecasting

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Knowledge-Based Systems 2025年 323卷

作者： Junjie Ye Jinhong Li Rui Su Sen Yang Yaqun Huang Chunna Zhao School of Information Science & Engineering Yunnan University Kunming Yunnan 650504 China Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming Yunnan 650500 China Department of Computer Science and Technology West Yunnan University of Applied Sciences Dali Yunnan 671000 China

Multivariate time series forecasting (MTSF) is of critical importance in various domains, including climate prediction, financial analysis, and energy management. Multivariate time series data typically exhibit both intra-series and inter-series dependencies, leading to intricate and intertwined relationships. Recently, numerous studies have focused on capturing both types of correlations. Most existing methods adopt a single-flow structure, attempting to capture features from both the time and variable dimensions simultaneously. However, due to the heterogeneous dependencies between the time dimension and variable dimension, single-flow structures are prone to interference in feature learning, making it difficult to effectively model complex dependencies. To address this issue, we propose a decoupled D ual- F low dynamic G raph C onvolutional N etwork (DFGCN) for MTSF, which separately models the intra-series and inter-series dependencies through decoupled feature learning. First, a dual-flow embedding layer is employed to separately represent the features of the time and variable dimensions. Next, we propose a dual-flow dynamic sparse GCN incorporating Pearson correlation, which robustly learns both intra-series and inter-series dynamic dependencies, while effectively reducing the computational cost of the GCN. Then, we introduce a dual-flow global attention layer, which separately learns the global information of inter-series and intra-series dependencies. By combining dynamic sparse GCN and the global attention mechanism, DFGCN is able to effectively model both local and global features in multivariate time series data. Experimental results on multiple real-world datasets show that DFGCN outperforms strong baseline models, with improvements ranging from 2.40% to 19.84%. Ablation experiments further validate the model’s robustness and the effectiveness of its components. Code is available at this repository: https://***/junjieyePhD/DFGCN .

关键词： Cost benefit analysis

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Progressive LiDAR Adaptation for Road Detection

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IEEE/CAA Journal of Automatica Sinica 2019年第3期6卷 693-702页

作者： Zhe Chen Jing Zhang Dacheng Tao IEEE the UBTECH Sydney Artificial Intelligence Centre and the School of Computer Science Faculty of Engineering and Information Technologies University of Sydney the School of Automation Hangzhou Dianzi University the University of Technology Sydney

Despite rapid developments in visual image-based road detection, robustly identifying road areas in visual images remains challenging due to issues like illumination changes and blurry images. To this end, LiDAR sensor data can be incorporated to improve the visual image-based road detection,because LiDAR data is less susceptible to visual noises. However,the main difficulty in introducing LiDAR information into visual image-based road detection is that LiDAR data and its extracted features do not share the same space with the visual data and visual features. Such gaps in spaces may limit the benefits of LiDAR information for road detection. To overcome this issue, we introduce a novel Progressive LiDAR adaptation-aided road detection(PLARD) approach to adapt LiDAR information into visual image-based road detection and improve detection performance. In PLARD, progressive LiDAR adaptation consists of two subsequent modules: 1) data space adaptation, which transforms the LiDAR data to the visual data space to align with the perspective view by applying altitude difference-based transformation; and 2) feature space adaptation, which adapts LiDAR features to visual features through a cascaded fusion structure. Comprehensive empirical studies on the well-known KITTI road detection benchmark demonstrate that PLARD takes advantage of both the visual and LiDAR information, achieving much more robust road detection even in challenging urban scenes. In particular, PLARD outperforms other state-of-theart road detection models and is currently top of the publicly accessible benchmark leader-board.

关键词： Autonomous driving computer vision deep learning LiDAR processing road detection

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A Novel Model for Context Conflict Resolution Basec on Set Pair Analysis

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China Communications 2014年第A02期11卷 70-78页

作者： DUO Lin LAI Xiaoyang LIU Zengli CHEN Xi School of Computer and Communication Engineering University of Science and Technology Beijing Beijing 100083 P.R. China Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming 650500 RR. China

Context-aware plays a pivotal role in the wisdom network of information processing. Due to the limited resources, context conflict is inevitable in context-aware. User satisfaction is a good reflection for the wisdom degree of the network. In this paper, considering the user satisfaction, we propose a novel context-aware conflict solution model based on set pair Analysis （SPA）. The model obtains the best server mode by the maximum satisfaction connection degree to solve the conflict in context-aware. The simulation analysis shows that the proposed method is effective and can solve many users competition for the same scene of conflict.

关键词： context-aware context conflict SPA satisfaction connection degree

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Design of automatic washing machine based on Verilog HDL language

Design of automatic washing machine based on Verilog HDL lan...

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International Conference on Electronics and Optoelectronics

作者： Chen, Xizhen Chen, Guangjian Jia, Jinling Yu, Han Zhou, Tianpeng Faculty of Automation and Information Sichuan University of Science and Engineering Zigong China Faculty of Computer Science Sichuan University of Science and Engineering Zigong China

ISBN: (纸本)9781612842738

As described by digital system the language Verilog HDL is widely used in the circuit design, its own advantages to be able to use software language describe hardware features that makes it has good readability, portability, etc. Its advantages not only reduce the hardware development cycle but also greatly reduce development costs. This article describes the characteristics and application of Verilog HDL and take the automatic washing machine as examples to illustrate the practicality of HDL. The result of simulation shows this method is feasibility and effectiveness. © 2011 IEEE.

关键词： computer hardware description languages

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Temperature control of electric furnace based on fuzzy PID

Temperature control of electric furnace based on fuzzy PID

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International Conference on Electronics and Optoelectronics

作者： Yu, Han Jia, Jinling Chen, Guangjian Chen, Xizhen Faculty of Automation and Information Sichuan University of Science and Engineering Zigong China Faculty of Computer Science Sichuan University of Science and Engineering Zigong China

ISBN: (纸本)9781612842738

To electric furnace's characters as non-linear and time-varying, we designed a fuzzy PID controller, and made some simulation through MATLAB, at the same time we used a traditional PID controller and simulated, then compared the result of traditional PID controller with fuzzy PID controller's result and analyzed the property. The result of simulation shows that the speediness, stability and anti-interference ability of fuzzy PID control are superior to those of traditional PID control. © 2011 IEEE.

关键词： MATLAB

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A particle swarm and neural network approach for position control of XY Piezo Actuator Stage

A particle swarm and neural network approach for position co...

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19th International Workshop on Robotics in Alpe-Adria-Danube Region, RAAD 2010

作者： Kusić, Dragan Čas, Jure Faculty of Electrical Engineering and Computer Science Institute of Automation University of Maribor Slovenia Faculty of Electrical Engineering and Computer Science Institute of Robotics University of Maribor Slovenia

ISBN: (纸本)9781424468867

This paper describes a position control of 2 degrees of freedom (DOF) XY Piezo Actuator Stage (XY PAS) with Feedforward Neural Network (FNN) and additional Particle Swarm Optimization (PSO) approach, which is used as an improved learning method for optimizing the weights of FNN rather than just the standard technique of back-propagation of errors. XY PAS is fabricated by a photo structuring process from micro-structured photosensitive glass and two piezo actuators (PEAs), which are built-on to meet the request for its precise movement on the working plane with approximate dimensions 60 by 60 micrometres. It is evident from the simulation model of XY PAS, that accurate positional control is an exact piece of work. The FNN is used as adaptive feedforward controller describing the estimated inverse function of XY PAS for each reference position of XY PAS's tip. Due to the optimal control performance of FNN, the PSO is introduced in order to improve the learning method of FNN. A simulation model of the XY PAS and the proposed FNN control algorithm with PSO have been developed in Matlab/Simulink. The obtained results show quick convergence capability and a satisfactory global search. © 2010 IEEE.

关键词： Position control

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