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Articles 6091 - 6120 of 11193

Full-Text Articles in Artificial Intelligence and Robotics

Research On The Overall Design And Key Technology Of “Human In The Loop” Synthetic Training Simulation, Zhiming Dong, Guangchao Zhu, Xiangzhong Xu, Yaxin Tan, Fan Rui Jun 2021

Research On The Overall Design And Key Technology Of “Human In The Loop” Synthetic Training Simulation, Zhiming Dong, Guangchao Zhu, Xiangzhong Xu, Yaxin Tan, Fan Rui

Journal of System Simulation

Abstract: Aiming at the difficulties of "human-in-the-loop" synthetic training simulation such as large scale, many entities, decentralized deployment and many heterogeneous systems. After study the construction of US Army synthetic training environment, a sustainable evolution cloud service architecture of distributed synthetic training simulation based on TISA middleware is designed, and a composable multi-level synthetic training simulation application model is put forward. It solves the technical problems of distributed training simulation, which are real-time interconnection and interoperability, consistency of battlefield environment, model composition and reuse, simulation as a service, etc. It provides technical supports for large-scale "human-in-the-loop" tactical confrontation exercises and …

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Dynamic Control Of Twin-Workshop Model Of Circuit Breaker Considering Takt Time Constraints, Shu Liang, Zhang Jie, Yanfang Yang, Yang Miao, Ziran Wu Jun 2021

Dynamic Control Of Twin-Workshop Model Of Circuit Breaker Considering Takt Time Constraints, Shu Liang, Zhang Jie, Yanfang Yang, Yang Miao, Ziran Wu

Journal of System Simulation

Abstract: The production takt time greatly impact on the twin system modeling of assembly line. A dynamic control method of the twin workshop model is proposed, which considers the takt time constraints is proposed. Detecting the motion of the circuit breaker unit and the assembly line system, and the dynamic motion model of the circuit breaker twins are developed based on the takt time calculation. Through driving force loading, motion logic script controlling and switching, the twin mapping of the assembly line system is realized with fixed and flexible takt time as well. The circuit breaker’s directional bounding boxes and …

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Research On Intrusion Detection Based On Stacked Autoencoder And Long-Short Memory, Lin Shuo, An Lei, Zhijun Gao, Shan Dan, Wenli Shang Jun 2021

Research On Intrusion Detection Based On Stacked Autoencoder And Long-Short Memory, Lin Shuo, An Lei, Zhijun Gao, Shan Dan, Wenli Shang

Journal of System Simulation

Abstract: As network attacks increasingly hidden, intelligent and complex. Simple machine learning cannot deal with attacks timely. A deep learning method based on the combination of SDAE and LSTM is proposed. Firstly, the distribution rules of network data are extracted intelligently layer by layer by SDAE, and the diverse anomaly features of high-dimensional data ate extracted by using coefficient penalty and reconstruction error of each coding layer. Then, LSTM’ s memory function and the powerful learning ability of sequence data are used to classify learning depth. Finally, the experiments are carried out with the UNSW-NB15 data set, which is analyzed …

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Creating Synthetic Satellite Cloud Data Based On Gan Method, Wencong Cheng, Xiaokang Shi, Zhigang Wang Jun 2021

Creating Synthetic Satellite Cloud Data Based On Gan Method, Wencong Cheng, Xiaokang Shi, Zhigang Wang

Journal of System Simulation

Abstract: To create the synthetic satellite cloud data in the domain of Meteorology, a method based on Generative Adversarial Networks (GAN) is proposed. Depending on ability of the nonlinear mapping and the information extraction of raster data with the deep learning network, a deep generative adversarial network model is proposed to extract the corresponding information between the numerical weather prediction(NWP) products and the satellite cloud data, and then the appropriate elements of the NWP product are chosen as the input to synthesize the corresponding satellite cloud data. The experiments are conducted on the re-analysis products of the European Centre …

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Research Of Super-Resolution Processing Of Invoice Image Based On Generative Adversarial Network, Xinli Li, Changming Zou, Guotian Yang, Liu He Jun 2021

Research Of Super-Resolution Processing Of Invoice Image Based On Generative Adversarial Network, Xinli Li, Changming Zou, Guotian Yang, Liu He

Journal of System Simulation

Abstract: Automatic identification of invoices can effectively improve financial efficiency. But low-resolution invoice image reduces the accuracy of automatic identification, an ESRGAN (Encoder Super-resolution Generative Adversarial Network) network for super-resolution processing of invoice images is proposed. The ESRGAN network is based on a conditional generative adversarial network. An auxiliary encoder is designed to guide the network to generate a more realistic super-resolution image. Based on the actual invoice image, the ESRGAN network and the conventional image processing, SRCNN (Super-resolution Convolutional Neural Networks) network and SRGAN (Super-resolution Generative Adversarial Network) network. The model is evaluated through two evaluation indicators of peak …

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Trajectory Tracking Control Of Robotic Manipulators Based On Smooth Second-Order Sliding Mode, Ruimin Zhang, Qiaoyu Chen Jun 2021

Trajectory Tracking Control Of Robotic Manipulators Based On Smooth Second-Order Sliding Mode, Ruimin Zhang, Qiaoyu Chen

Journal of System Simulation

Abstract: The robotic manipulators have characteristics of strong nonlinearity, strong coupling, multiple input and output, uncertainties, and so on. It is necessary to proposed a multivariable smooth second-order sliding mode trajectory tracking control method. The method can eliminate the chattering in the conventional sliding mode control and increase convergence speed. The property of finite time convergency is proved by the Lyapunov stability theory. Furthermore, the method is applied for the tracking control of two-joint robotic manipulators with model uncertainty and external disturbances. The simulation results show that the proposed method is effective and has high control precision and strong robustness.

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Research On Digital Protection System Of Intangible Cultural Heritage Based On Mobile Augmented Reality Technology, Shouming Hou, Ge Qian, Yanyan Liu Jun 2021

Research On Digital Protection System Of Intangible Cultural Heritage Based On Mobile Augmented Reality Technology, Shouming Hou, Ge Qian, Yanyan Liu

Journal of System Simulation

Abstract: Aiming at the problem of the single form and poor interaction of intangible cultural heritage protection, a non-heritage digital online display system is designed and implemented based on mobile augmented reality technology. Taking clay sculpture non-heritage protection as an example, the main functional modules of the system cloud and mobile terminal are designed. Based on a combination of 3D scanning and iterative mesh simplification, a fast modeling method is proposed. ORB-FV and optical flow tracking algorithm are used for online recognition and tracking registration of images. The system is developed based on Unity3D. The test results show that, …

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Fault Diagnosis Of Mechanical Equipment Based On Ga-Svr With Missing Data In Small Samples, Jingjing Wei, Qinming Liu, Chunming Ye, Guanlin Li Jun 2021

Fault Diagnosis Of Mechanical Equipment Based On Ga-Svr With Missing Data In Small Samples, Jingjing Wei, Qinming Liu, Chunming Ye, Guanlin Li

Journal of System Simulation

Abstract: In view of the equipment fault diagnosis with small and missing sample data, a method of missing data filling based on support vector regression optimized by genetic algorithm is proposed to improve the accuracy of equipment fault diagnosis. The support vector regression optimized by genetic algorithm was trained by other data values of missing data, and univariate prediction results were obtained. The training set was reconstructed through correlation analysis, so as to obtain the multivariate prediction results. Dynamic weights were established to combine univariate prediction results and multivariate prediction results to fill in the missing data. The …

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Active Learning Intelligent Soft Sensor Based On Probability Selection, Xuezhi Dai, Weili Xiong Jun 2021

Active Learning Intelligent Soft Sensor Based On Probability Selection, Xuezhi Dai, Weili Xiong

Journal of System Simulation

Abstract: Aiming at lack of tag samples and high cost of sampling tags in complex industrial processes, an active learning algorithm based on probability selection is proposed. Firstly, unlabeled samples are performed subspace integration by using the principal component analysis. Then, the information of unlabeled samples is evaluated by the uncertainty, which is calculated based on the out put of all sub learners. And the most valuable samples are selected to mark manually. Finally, the function of unlabeled samples and labeled samples are analyzed, and the termination conditions are designed by introducing the performance index of training set. Through simulations …

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Virtual Training System For Spacecraft Maintenance Based On Desktop Virtual Reality, Shisong Wei, Zhengdong Zhou, Xuling Zhang, Mao Ling, Junshan Jia, Chuanle Liu Jun 2021

Virtual Training System For Spacecraft Maintenance Based On Desktop Virtual Reality, Shisong Wei, Zhengdong Zhou, Xuling Zhang, Mao Ling, Junshan Jia, Chuanle Liu

Journal of System Simulation

Abstract: In order to shorten the training period of aerospace maintenance personnel and improve their operation proficiency, a spacecraft maintenance simulation system based on the desktop virtual reality technology is designed and developed. It is superior to the head-mounted display, which is bulky, isolated from the real world, easy to make users dizzy and hard to be shared. The assembly management scheme based on XMind and SqlServer database is proposed to realize the visualization of assembly rule editing, which makes assembly and disassembly flexible and convenient.

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Technical Characteristics Of Digital Twins And Application Prospects In The Field Of Flight Testing, Liu Yu, Xie Qiang Jun 2021

Technical Characteristics Of Digital Twins And Application Prospects In The Field Of Flight Testing, Liu Yu, Xie Qiang

Journal of System Simulation

Abstract: For the application of digital twins in flight tests, the connotation and technical characteristics of digital twins were studied and analyzed. Six flight test digital twins typical application scenarios, such as the requirements development and overall planning of flight test, the flight test mission designing, the integrated testing and modification of flight test, the flight test organization and implementation, the fast maintenance and support and the training of flight test engineers have been designed by mapping the behavior and performance of flight test objects. The synchronize updates, parallel validation and spiral evolution were achieved between the digital models …

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Research On The Offset Of Elliptical Quiet Zone In Catr Of Multiple Feed, Liu Yong, Liwei Guo, Wangyang Song, Jiang Xing, Simin Li, Peng Lin Jun 2021

Research On The Offset Of Elliptical Quiet Zone In Catr Of Multiple Feed, Liu Yong, Liwei Guo, Wangyang Song, Jiang Xing, Simin Li, Peng Lin

Journal of System Simulation

Abstract: Electromagnetic target simulator based on CATR of the quiet zone movement,which adopt the multi-feed source CATR RF signal feeding by reflecting to get the quiet zone movement of simulated far field. It can be used in simulation of seekers in a multi-target mobile environment. The phase of the feeds of the 1×4 horn array is changed to realize the movement of the quiet zone in the CATR. The phase consistency of the millimeter wave quiet zone of the target simulation system determines the target simulation accuracy. The amplitude and phase characteristics of the array feeding with different beam …

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Energy Management Of Marine Current Power Generation System Based On Fuzzy Logical Control, Jingang Han, Li Xu Jun 2021

Energy Management Of Marine Current Power Generation System Based On Fuzzy Logical Control, Jingang Han, Li Xu

Journal of System Simulation

Abstract: The fluctuation of marine current velocity leads to the fluctuation of power generation. The hybrid energy storage system composed of vanadium redox flow battery and super capacitor is used to improve the power quality and smooth the marine current power generation. With the research and commercialization of large scale power marine current power generation system, the capacity of energy storage system has been increasing. To reduce the rated capacity of super capacitor banks in energy storage system, an energy management strategy based on low-pass filter optimization algorithm of fuzzy control is proposed and the simulation model of 3 MW …

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Development Of Semi-Physical Simulation Platform For Monitoring Municipal Solid Waste Incineration Process, Aijun Yan, Xia Heng, Xizhi Liu Jun 2021

Development Of Semi-Physical Simulation Platform For Monitoring Municipal Solid Waste Incineration Process, Aijun Yan, Xia Heng, Xizhi Liu

Journal of System Simulation

Abstract: In order to research and test the modeling, control and optimization of MSW (Municipal Solid Waste) incineration process, a semi-physical simulation platform with three-layer structure by combining the physical control system with the virtual object is developed. The physical control system of the platform is composed of an intelligent control optimization layer and basic control layer; and the virtual object layer includes simulated instrument, actuator and incineration process model. The software for man-machine interface with OPC (Object Linking and Embedding (OLE) for Process Control), equipment/parameter monitoring, and incineration process model are developed. The functions of intelligent control optimization layer …

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Development Paths Of New Energy Vehicles Incorporating Co2 Emissions Trading Scheme, Wenxiang Li, Li Ye, Jieshuang Dong, Yiming Li Jun 2021

Development Paths Of New Energy Vehicles Incorporating Co2 Emissions Trading Scheme, Wenxiang Li, Li Ye, Jieshuang Dong, Yiming Li

Journal of System Simulation

Abstract: New energy vehicles in China have entered the “post-subsidy era”, and it is urgent to explore and establish a long-term mechanism for market-oriented development. The CO2 emission trading scheme for road transport (ETS-RT) is introduced to replace financial subsidies, forming a market-oriented incentive and punishment mechanism. Therefore, a market mechanism is established where internal combustion engine vehicles feed new energy vehicles. A causal loop diagram of system dynamics was used to analyze the key policy parameters of the ETS-RT that affect the development of new energy vehicles. Then a multi-agents-based model of ETS-RT is established to simulate the …

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Review On Key Technologies Of Industrial Control System Security Simulation, Bailing Wang, Hongri Liu, Yaofang Zhang, Sicai Lü, Zibo Wang, Qimeng Wang Jun 2021

Review On Key Technologies Of Industrial Control System Security Simulation, Bailing Wang, Hongri Liu, Yaofang Zhang, Sicai Lü, Zibo Wang, Qimeng Wang

Journal of System Simulation

Abstract: In order to cope with the increasingly serious industrial internet security problems, simulation is viewed as a critical backboned technology for drilling of network attack and defense, tracking back and analyzing of security incidents, as well as validating of pre-research technology. On the basis of summarizing the studies of three types of typical industrial control system security simulation platform, the key technologies used in industrial control cyber range and industrial control honeynets are highlighted. Technologies are summarized, such as the virtualization technology of industrial control network and industrial control components, the construction technology of industrial control target field dominated …

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Adaptive Network Slicing In Fog Ran For Iot With Heterogeneous Latency And Computing Requirements: A Deep Reinforcement Learning Approach, Almuthanna Nassar Jun 2021

Adaptive Network Slicing In Fog Ran For Iot With Heterogeneous Latency And Computing Requirements: A Deep Reinforcement Learning Approach, Almuthanna Nassar

USF Tampa Graduate Theses and Dissertations

In view of the recent advances in Internet of Things (IoT) devices and the emerging new breed of smart city applications and intelligent vehicular systems driven by artificial intelligence, fog radio access network (F-RAN) has been recently introduced for the next generation wireless communications. The capability of F-RAN has emerged to overcome the latency limitations of cloud-RAN (C-RAN) and assure the quality-of-service (QoS) requirements of the ultra-reliable-low-latency-communication (URLLC) for IoT applications. To this end, fog nodes (FNs) are equipped with computing, signal processing and storage capabilities to extend the inherent operations and services of the cloud to the edge. However, …

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Optimization And Machine Learning Methods For Solving Combinatorial Problems In Urban Transportation, Aigerim Bogyrbayeva Jun 2021

Optimization And Machine Learning Methods For Solving Combinatorial Problems In Urban Transportation, Aigerim Bogyrbayeva

USF Tampa Graduate Theses and Dissertations

This dissertation investigates three applications of emerging technologies for urban trans- portation. In the first chapter, we design a new market for fractional ownership of au- tonomous vehicles (AVs), in which an AV is co-leased by a group of individuals. We present a practical iterative auction based on the combinatorial clock auction to match the interested customers together and determine their payments. In designing such an auction, we con- sider continuous-time items (time slots) which are defined by bidders, and naturally exploit driverless mobility of AVs to form co-leasing groups. To relieve the computational burdens of both bidders and the …

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Flying Free: A Research Overview Of Deep Learning In Drone Navigation Autonomy, Thomas Lee, Susan Mckeever, Jane Courtney Jun 2021

Flying Free: A Research Overview Of Deep Learning In Drone Navigation Autonomy, Thomas Lee, Susan Mckeever, Jane Courtney

Articles

With the rise of Deep Learning approaches in computer vision applications, significant strides have been made towards vehicular autonomy. Research activity in autonomous drone navigation has increased rapidly in the past five years, and drones are moving fast towards the ultimate goal of near-complete autonomy. However, while much work in the area focuses on specific tasks in drone navigation, the contribution to the overall goal of autonomy is often not assessed, and a comprehensive overview is needed. In this work, a taxonomy of drone navigation autonomy is established by mapping the definitions of vehicular autonomy levels, as defined by the …

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Automated Decision Making And Machine Learning: Regulatory Alternatives For Autonomous Settings, Alyssa Heminger Jun 2021

Automated Decision Making And Machine Learning: Regulatory Alternatives For Autonomous Settings, Alyssa Heminger

University Honors Theses

Given growing investment capital in research and development, accompanied by extensive literature on the subject by researchers in nearly every domain from civil engineering to legal studies, automated decision-support systems (ADM) are likely to see a place in the foreseeable future. Artificial intelligence (AI), as an automated system, can be defined as a broad range of computerized tasks designed to replicate human neural networks, store and organize large quantities of information, detect patterns, and make predictions with increasing accuracy and reliability. By itself, artificial intelligence is not quite science-fiction tropes (i.e. an uncontrollable existential threat to humanity) yet not without …

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Artificial Intelligence (Ai) And Augmented Reality (Ar): Disambiguated In The Telemedicine / Telehealth Sphere, Sharon L. Burton Jun 2021

Artificial Intelligence (Ai) And Augmented Reality (Ar): Disambiguated In The Telemedicine / Telehealth Sphere, Sharon L. Burton

Publications

The world is navigating through unfamiliar and incomprehensible times – COVID-19, international economic crisis, and crumbling healthcare systems. The United States (US) healthcare industry is grappling with an increased workload and advancing digitization technological concerns. The failure of organizations to offer suitable cybersecurity controls within the critical infrastructure leads to advanced persistent threat (APT) that could have incapacitating effects on organizations. A keen understanding of cybersecurity is vital for leaders and the need is referenced in US policy that advances a national unity of effort to strengthen and maintain secure, functioning, and resilient critical infrastructure. Akin to the Presidential Policy …

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Algebraic Graph-Assisted Bidirectional Transformers For Molecular Property Prediction, Dong Chen, Kaifu Gao, Duc Duy Nguyen, Xin Chen, Yi Jiang, Guo-Wei Wei, Feng Pan Jun 2021

Algebraic Graph-Assisted Bidirectional Transformers For Molecular Property Prediction, Dong Chen, Kaifu Gao, Duc Duy Nguyen, Xin Chen, Yi Jiang, Guo-Wei Wei, Feng Pan

Mathematics Faculty Publications

The ability of molecular property prediction is of great significance to drug discovery, human health, and environmental protection. Despite considerable efforts, quantitative prediction of various molecular properties remains a challenge. Although some machine learning models, such as bidirectional encoder from transformer, can incorporate massive unlabeled molecular data into molecular representations via a self-supervised learning strategy, it neglects three-dimensional (3D) stereochemical information. Algebraic graph, specifically, element-specific multiscale weighted colored algebraic graph, embeds complementary 3D molecular information into graph invariants. We propose an algebraic graph-assisted bidirectional transformer (AGBT) framework by fusing representations generated by algebraic graph and bidirectional transformer, as well as …

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Development And Prospect Of Simulation Research In China, Xiaogang Qiu, Duan Hong, Xie Xu, Mengna Zhu Jun 2021

Development And Prospect Of Simulation Research In China, Xiaogang Qiu, Duan Hong, Xie Xu, Mengna Zhu

Journal of System Simulation

Abstract: It is important to treat modeling and simulation (M&S) as a discipline to advance its development. In China, M&S has been researched and applied over 40 years, and is gradually becoming an independent discipline. Modeling and simulating the complex systems are the challenge, however, this also brings grand opportunity for M&S to widen and improve itself. Since 1980s, the M&S community in China has realized the broad applications of M&S, comprehended M&S from multiple perspectives, conducted extensive research on basic questions, and discussed the composition of the basic simulation theory. By summarizing these achievements, the future works that have …

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Multiple Object Tracking And Kinematic Simulation For Short Track Speed Skating, Li Qi, Hanlin Mo, Xiangdong Wang, Li Hua Jun 2021

Multiple Object Tracking And Kinematic Simulation For Short Track Speed Skating, Li Qi, Hanlin Mo, Xiangdong Wang, Li Hua

Journal of System Simulation

Abstract: Aiming at the problem that it is difficult to obtain the motion data of each athlete in the short track speed skating competition, an algorithm flow of multiple object tracking and kinematic simulation is proposed. A local matching metric is proposed to deal with the partial occlusion in monocular video and improve the tracking stability and robustness. The motion simulation method based on homography mapping and derivative of fitted curve is realized to estimate kinematic parameters such as velocity and acceleration. The experiments on Skating Track Multiple ObjectTracking (STMOT) verified the effectiveness and superiority of the proposed methods.

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Decomposition Furnace Outlet Temperature Prediction Based On Elasticnet And Lstm, Guangyu Yu, Xueping Dong, Xiangmin Wang, Gan Min Jun 2021

Decomposition Furnace Outlet Temperature Prediction Based On Elasticnet And Lstm, Guangyu Yu, Xueping Dong, Xiangmin Wang, Gan Min

Journal of System Simulation

Abstract: The outlet temperature of the decomposition furnace is a key indicator in the cement production process. Aiming at the problem that traditional prediction methods only consider the influence of wind, coal, and materials, a temperature prediction model of ElasticNet combined with Long Short-Term Memory (LSTM) neural network is proposed. The ElasticNet-LSTM export temperature prediction model is constructed by using the ElasticNet method to estimate the parameters of different variables, fully considering the influencing factors and realizing the variable screening, and analyzing the influence of the number of hidden layers and nodes on the accuracy of the neural network. Simulation …

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A Shared Memory Based Parallel Hierarchical Interest Matching Algorithm, Wenjie Tang, Junwei Cheng, Yiping Yao, Zhu Feng Jun 2021

A Shared Memory Based Parallel Hierarchical Interest Matching Algorithm, Wenjie Tang, Junwei Cheng, Yiping Yao, Zhu Feng

Journal of System Simulation

Abstract: Interest matching plays an important role in distributed simulation. However, because of huge number of simulation entities and frequent change of regions, interest matching consumes tremendous computation in large scale simulations. The ubiquity of multicore urges us to improve the performance of interest matching by parallelization. A shared memory based parallel hierarchical interest matching algorithm is propose to solve the problem. It maps subscribe regions into a full binary tree, and compares update regions with the tree in parallel. Due to the associative relationship between adjacent nodes, unnecessary comparisons can be eliminated. The experimental results demonstrate that the …

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Time-Delay Estimation For Mimo Delay Systems With Unknown Structures, Xuguang Wang, Mengjie Feng, Su Jie, Jiale Quan Jun 2021

Time-Delay Estimation For Mimo Delay Systems With Unknown Structures, Xuguang Wang, Mengjie Feng, Su Jie, Jiale Quan

Journal of System Simulation

Abstract: In the unknown-structure delay system modeling, time-delays lead to a mismatch between the system inputs and outputs on the timeline and cause low system modeling accuracy. A time-delay estimation method is proposed for the unknown-structure MIMO (Multiple-Input Multiple-Output) delay systems. A general mathematical description is given from the algebraic point of view, the delay correlation function is defined, and a quantitative constraint between system input-output and time-delay is constructed. A greedy time-delay search algorithm is introduced based on the delay correlation function. Simulation experiments and real data experiments show the availability of the proposed method.

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Fault Detection Of Wind Turbine Bearing Based On Bo-Sdae Multi-Source Signal, Dinghui Wu, Zhichao Zhu, Xinhong Han Jun 2021

Fault Detection Of Wind Turbine Bearing Based On Bo-Sdae Multi-Source Signal, Dinghui Wu, Zhichao Zhu, Xinhong Han

Journal of System Simulation

Abstract: Due to the discrepancy within signals from sensors of wind turbines caused by environmental interference, the fault detection results of wind turbine bearing will be affected and the multi-source signal fault diagnosis method is proposed to improve the reliability of fault detection. The time-domain and frequency-domain features of bearing vibration signals, noise signals and temperature signals are used for feature extraction,and then the features are transmitted to the stacked denoising autoencoders, which are optimized the hidden layer node structure by the Bayesian optimization algorithm to achieve multi-source signal feature fusion. Softmax function is used for classification. Experiments show that …

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Rapid Development Technology Of Virtual Maintenance Training Simulation Model For Aviation Equipment, Rongqiang Li, Aibing Wen, Bin Hua, Jiajun Li, Jiang Bing Jun 2021

Rapid Development Technology Of Virtual Maintenance Training Simulation Model For Aviation Equipment, Rongqiang Li, Aibing Wen, Bin Hua, Jiajun Li, Jiang Bing

Journal of System Simulation

Abstract: Taking the practical application of the aircraft virtual maintenance training as the demand, the basic development process and technical means of the aircraft virtual maintenance training simulation model are analyzed, which solves the technical bottleneck in the popularization and application of the large-scale engineering. Aiming at the crucial problems such as the low efficiency in the development of maintenance training simulation model and the difficulties in updating the model, a rapid development process to support the large-scale engineering applications is proposed. The principles and implementation ways of three key technologies supporting the rapid development of virtual maintenance training simulation …

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Day-Ahead Dispatching Model Of Source-Load Coordination Based On Response Behavior To Real-Time Pricing, Liu Yun, Han Song, Qiuli Huang Jun 2021

Day-Ahead Dispatching Model Of Source-Load Coordination Based On Response Behavior To Real-Time Pricing, Liu Yun, Han Song, Qiuli Huang

Journal of System Simulation

Abstract: In order to give full play to the regulating role of electricity price on the market, considering the difference of consumers' response behavior to real-time pricing, consumers are divided into short-term consumers, mixed consumers and long-term consumers, and the real-time pricing models of three types of consumers are constructed based on the electricity price elasticity matrix. On this basis, a day-ahead dispatching model of source-load coordination based on consumer’s response behavior to real-time pricing is established. With the help of the MOST toolkits in MATPOWER and the Mosek solver, the arithmetic analysis is developed in a modified IEEE 57-buses …

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