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Task Allocation Method For Multi-Uav Cooperative Reconnaissance In Complex Environment, Fuzhen Zhang, Yaoqin Zhu 2022 School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China;

Task Allocation Method For Multi-Uav Cooperative Reconnaissance In Complex Environment, Fuzhen Zhang, Yaoqin Zhu

Journal of System Simulation

Abstract: The existing cooperative planning methods of multiple UAVs often carry out path planning and task allocation separatly, which causes the cooperative scheme not being the best in a complex environment. The cost matrix of multi-UAV cooperative reconnaissance on heterogeneous targets is established. Aiming at the various obstacle constraints and the characteristics of UAV motion and track in complex environment, an improved PSO-AFSA is used to solve the single UAV track planning model. Hungarian algorithm is used to complete the cooperative allocation of reconnaissance tasks of UAVs. The simulation results show that the algorithm can make the flying range of …


Simulation Of Emergency Medical Materials Collaborative Distribution Considering Supplier Clustering, Zhe Wang, Hongyuan Shao, Zihao Cong, Wenwen Ma 2022 1.China Research Center for Emergency Management, Wuhan University of Technology, Wuhan 430070, China;2.School of Safety Science and Emergency Management, Wuhan University of Technology, Wuhan 430070, China;

Simulation Of Emergency Medical Materials Collaborative Distribution Considering Supplier Clustering, Zhe Wang, Hongyuan Shao, Zihao Cong, Wenwen Ma

Journal of System Simulation

Abstract: Aiming at the insufficient local government medical material reserves and low distribution efficiency to public health emergencies, consider supplier clustering a two-stage emergency medical supplies public-private collaborative location and alloation model is designed. In for disaster preparedness, fuzzy clustering algorithm to realize supplier clustering, and a cooperation mechanism with the government is establish realize the joint storage of emergency medical supplies; In the early stage of rescue, relying on the government and various suppliers' material storage and transportation capabilities, a location allocation simulation model to minimize the weighted sum of total logistics cost and demand unsatisfied rate is …


Research On High-Performance Emulation Technology Of Starlink Constellation Based On Cloud Platform, Yuan Liu, Xinyi Xue, Xiaofeng Wang 2022 School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi 214122, China;

Research On High-Performance Emulation Technology Of Starlink Constellation Based On Cloud Platform, Yuan Liu, Xinyi Xue, Xiaofeng Wang

Journal of System Simulation

Abstract: Network emulation on Starlink constellation is an important verification and evaluation tool for the design and construction of low earth orbit constellations in the future. Aiming at the characteristics of large-scale and complex structure of the Starlink network, a high-performance satellite network emulation system is designed. Based on the distributed network emulation architecture of cloud platform, through the development of STK Engine underlying interface, satellite model library storage optimization and asynchronous message transmission technology, the rapid deployment of Starlink constellation is carried out, and has good scalability. The experimental results show that the proposed method can carry out …


Analysis And Research On End-To-End Optical Image Quality Of Large Aperture Off-Axis Space Telescope, Zhang Ban, Xiaobo Li, Xun Yang, Yuxi Jiang 2022 Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China;

Analysis And Research On End-To-End Optical Image Quality Of Large Aperture Off-Axis Space Telescope, Zhang Ban, Xiaobo Li, Xun Yang, Yuxi Jiang

Journal of System Simulation

Abstract: In order to evaluate the image quality of space on orbit telescope under the comprehensive constraints, the chain calculation analysis method is adopted. The main error factors of the optical image quality degradation are divided into six static errors and two dynamic errors. After calculation, the optical system wavefront aberration under the static loading error is reduced to 0.057λ on average. Under the influence of the static and dynamic errors, the 80% energy concentration of point spread function increases gradually. The method can be used to analyze and evaluate the influence of image stabilization control and precise temperature …


Towards Qos-Based Embedded Machine Learning, Tom Springer, Erik Linstead, Peiyi Zhao, Chelsea Parlett-Pelleriti 2022 Chapman University

Towards Qos-Based Embedded Machine Learning, Tom Springer, Erik Linstead, Peiyi Zhao, Chelsea Parlett-Pelleriti

Engineering Faculty Articles and Research

Due to various breakthroughs and advancements in machine learning and computer architectures, machine learning models are beginning to proliferate through embedded platforms. Some of these machine learning models cover a range of applications including computer vision, speech recognition, healthcare efficiency, industrial IoT, robotics and many more. However, there is a critical limitation in implementing ML algorithms efficiently on embedded platforms: the computational and memory expense of many machine learning models can make them unsuitable in resource-constrained environments. Therefore, to efficiently implement these memory-intensive and computationally expensive algorithms in an embedded computing environment, innovative resource management techniques are required at the …


Machine Learning To Predict Warhead Fragmentation In-Flight Behavior From Static Data, Katharine Larsen 2022 Embry-Riddle Aeronautical University

Machine Learning To Predict Warhead Fragmentation In-Flight Behavior From Static Data, Katharine Larsen

Doctoral Dissertations and Master's Theses

Accurate characterization of fragment fly-out properties from high-speed warhead detonations is essential for estimation of collateral damage and lethality for a given weapon. Real warhead dynamic detonation tests are rare, costly, and often unrealizable with current technology, leaving fragmentation experiments limited to static arena tests and numerical simulations. Stereoscopic imaging techniques can now provide static arena tests with time-dependent tracks of individual fragments, each with characteristics such as fragment IDs and their respective position vector. Simulation methods can account for the dynamic case but can exclude relevant dynamics experienced in real-life warhead detonations. This research leverages machine learning methodologies to …


Explanation Guided Contrastive Learning For Sequential Recommendation, Lei WANG, Ee-peng LIM, Zhiwei LIU, Tianxiang ZHAO 2022 Singapore Management University

Explanation Guided Contrastive Learning For Sequential Recommendation, Lei Wang, Ee-Peng Lim, Zhiwei Liu, Tianxiang Zhao

Research Collection Lee Kong Chian School Of Business

Recently, contrastive learning has been applied to the sequential recommendation task to address data sparsity caused by users with few item interactions and items with few user adoptions. Nevertheless, the existing contrastive learning-based methods fail to ensure that the positive (or negative) sequence obtained by some random augmentation (or sequence sampling) on a given anchor user sequence remains to be semantically similar (or different). When the positive and negative sequences turn out to be false positive and false negative respectively, it may lead to degraded recommendation performance. In this work, we address the above problem by proposing Explanation Guided Augmentations …


Pruning The Communication Bandwidth Between Reinforcement Learning Agents Through Causal Inference: An Innovative Approach To Designing A Smart Grid Power System, Xianjie ZHANG, Yu LIU, Wenjun LI, Chen GONG 2022 Dalian University of Technology

Pruning The Communication Bandwidth Between Reinforcement Learning Agents Through Causal Inference: An Innovative Approach To Designing A Smart Grid Power System, Xianjie Zhang, Yu Liu, Wenjun Li, Chen Gong

Research Collection School Of Computing and Information Systems

Electricity demands are increasing significantly and the traditional power grid system is facing huge challenges. As the desired next-generation power grid system, smart grid can provide secure and reliable power generation, and consumption, and can also realize the system’s coordinated and intelligent power distribution. Coordinating grid power distribution usually requires mutual communication between power distributors to accomplish coordination. However, the power network is complex, the network nodes are far apart, and the communication bandwidth is often expensive. Therefore, how to reduce the communication bandwidth in the cooperative power distribution process task is crucially important. One way to tackle this problem …


Equivariance And Invariance Inductive Bias For Learning From Insufficient Data, Tan WANG, Qianru SUN, Sugiri PRANATA, Karlekar JAYASHREE, Hanwang ZHANG 2022 Nanyang Technological University

Equivariance And Invariance Inductive Bias For Learning From Insufficient Data, Tan Wang, Qianru Sun, Sugiri Pranata, Karlekar Jayashree, Hanwang Zhang

Research Collection School Of Computing and Information Systems

We are interested in learning robust models from insufficient data, without the need for any externally pre-trained model checkpoints. First, compared to sufficient data, we show why insufficient data renders the model more easily biased to the limited training environments that are usually different from testing. For example, if all the training "swan" samples are "white", the model may wrongly use the "white" environment to represent the intrinsic class "swan". Then, we justify that equivariance inductive bias can retain the class feature while invariance inductive bias can remove the environmental feature, leaving only the class feature that generalizes to any …


Class Is Invariant To Context And Vice Versa: On Learning Invariance For Out-Of-Distribution Generalization, Jiaxin QI, Kaihua TANG, Qianru SUN, Xian-Sheng HUA, Hanwang ZHANG 2022 Nanyang Technological University

Class Is Invariant To Context And Vice Versa: On Learning Invariance For Out-Of-Distribution Generalization, Jiaxin Qi, Kaihua Tang, Qianru Sun, Xian-Sheng Hua, Hanwang Zhang

Research Collection School Of Computing and Information Systems

Out-Of-Distribution generalization (OOD) is all about learning invariance against environmental changes. If the context in every class is evenly distributed, OOD would be trivial because the context can be easily removed due to an underlying principle: class is invariant to context. However, collecting such a balanced dataset is impractical. Learning on imbalanced data makes the model bias to context and thus hurts OOD. Therefore, the key to OOD is context balance.We argue that the widely adopted assumption in prior work—the context bias can be directly annotated or estimated from biased class prediction—renders the context incomplete or even incorrect. In contrast, …


Dynamic Return Relationships In The Market For Cryptocurrency: A Var Approach, Julian Gouffray 2022 James Madison University

Dynamic Return Relationships In The Market For Cryptocurrency: A Var Approach, Julian Gouffray

James Madison Undergraduate Research Journal (JMURJ)

This paper examines how the Bitcoin-altcoin return relationship has evolved in periods between 2015 and 2020. To understand this relation, we observe data on the cryptocurrency Bitcoin and prominent altcoins Ethereum, Litecoin, Ripple, Stellar, and Monero, which collectively represent over 90% of the market throughout the observed period. We employ a vector autoregressive model (VAR) to produce forecast error variance decompositions, orthogonal impulse response functions, and Granger-causality tests. We find evidence that Bitcoin return variation has increasingly explained altcoin returns and that market inefficiency increased between 2017 and 2020, as shown by increased Granger causality between Bitcoin and altcoins. These …


Parallel Simulation System Of Equipment Precision Maintenance Based On Cloud-Edge-End Architecture, Yanqiang Di, Ting Li, Shaochong Feng, Qiongyao Liu, Jianhong Lü, Zhijia Chen, Yang Zhang, Pengfei Cao 2022 Shijiazhuang Campus, Army Engineering University, Shijiazhuang 050003, China;

Parallel Simulation System Of Equipment Precision Maintenance Based On Cloud-Edge-End Architecture, Yanqiang Di, Ting Li, Shaochong Feng, Qiongyao Liu, Jianhong Lü, Zhijia Chen, Yang Zhang, Pengfei Cao

Journal of System Simulation

Abstract: Aiming at the demands of equipment precision maintenance, based on the previous research results of equipment parallel simulation, the algorithm of equipment remaining useful life (RUL)prediction is optimized and a parallel simulation system for equipment precision maintenance with cloud-edge-end architecture is designed. At the equipment end, the system collects equipment status data and preprocesses it with edge devices. At the cloud end, based on simulation model, in parallel with the equipment entity, the system dynamically predicts the RUL of equipment. The prediction results are applied to the formulation and deduction of equipment maintenance plans to support the equipment …


Unmanned Air Vehicles Launching Aircraft Combat System And Key Technologies For Penetrating Counterair, Minghao Li, Wenhao Bi, An Zhang, Wenxuan Sun 2022 School of Aeronautics, Northwestern Polytechnical University, Xi’an 710072, China;

Unmanned Air Vehicles Launching Aircraft Combat System And Key Technologies For Penetrating Counterair, Minghao Li, Wenhao Bi, An Zhang, Wenxuan Sun

Journal of System Simulation

Abstract: Penetrating counterair is an important countermeasure to the anti-access/area denial environment. Under this operational requirement, the unmanned air vehicles launching aircraft (UAVLA)has received much attention due to the advantages of load quantity and variety, operational range and duration, and development time and cost. Based on the review of the concept development and supporting research related to the UAVLA, the top-level concepts of operations such as the component systems,operational process, operational events tracking, and information interaction of the UAVLA combat system (UAVLACS) are designed. The key technologies of the system are prospected from four aspects:intelligent cognition of battlefield situation under …


Opnet Based Simulation Of Hybrid Tdma Protocol For Helicopters Datalink, Yanfang Fu, Nan Zhang, Jianing Wei, Shaochun Qu, Ying Lu, Chang Liu 2022 1.School of Computer Science and Engineering Xi’an Technological University, Xi’an 710021, China;

Opnet Based Simulation Of Hybrid Tdma Protocol For Helicopters Datalink, Yanfang Fu, Nan Zhang, Jianing Wei, Shaochun Qu, Ying Lu, Chang Liu

Journal of System Simulation

Abstract: For the current time slot allocation problem of the data link, an improved hybrid time slot allocation protocol based on grey relational analysis is proposed and implemented. Through the aggregation of throughput, delay and load of current message buffer by grey relational analysis, the comprehensive evaluation index is obtained, and the time slot is allocated dynamically. The fixed time slot allocation is also adopted to ensure that at least one time slot is available for nodes in the network.Simulation results show that compared with the fixed TDMA(time division multiple access) protocol and the P-TDMA(priority-TDMA) protocol, the proposed protocol …


Research On Opponent Modeling Framework For Multi-Agent Game Confrontation, Junren Luo, Wanpeng Zhang, Weilin Yuan, Zhenzhen Hu, Shaofei Chen, Jing Chen 2022 College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410073, China;

Research On Opponent Modeling Framework For Multi-Agent Game Confrontation, Junren Luo, Wanpeng Zhang, Weilin Yuan, Zhenzhen Hu, Shaofei Chen, Jing Chen

Journal of System Simulation

Abstract: As the key technology of multi-agent game confrontation, opponent modeling is a typical cognitive modeling method of agent's behavior. Several typical models of multi-agent game confrontation,non-stationary problems, and meta-game theory are introduced; opponent modeling methods that concludes the frontier theory of opponent modeling are summarized, and the applications and challenges are analyzed. Based on the theory of meta-game, a general opponent modeling framework is constructed with three modules: opponent policy recognition and generation, opponent policy space reconstruction,and opponent exploitation. It is expected to provide theoretical and methodological reference for opponent modeling in multi-agent game confrontation.


Siamese Object Tracking Algorithm Combined With The Intersection Over Union Loss, Wei Zhou, Yuxiang Liu, Guangping Liao, Xin Ma 2022 Xiangtan University, School of Computer Science & School of Cyberspace Science, Xiangtan 411105, China;

Siamese Object Tracking Algorithm Combined With The Intersection Over Union Loss, Wei Zhou, Yuxiang Liu, Guangping Liao, Xin Ma

Journal of System Simulation

Abstract: To improve the accuracy of the object bounding box regression prediction of the SiamRPN,solve the problem of low discrimination of positive samples in classification prediction and the lack of correlation between regression prediction and classification prediction, an improved object tracking algorithm of SiamRPN which combined with IoU(intersection over union) loss is proposed. A joint optimization module of IoU-smooth L1 is designed to optimize the IoU loss of the best positive sample and the smooth L1 loss of other positive samples jointly. According to the regression prediction results, the weighted classification prediction is performed on the positive samples with the …


Relative-Residual-Based Dynamic Schedule For Decoding Of Ldpc Codes, Fatang Chen, Hebin Li, Zhihao Zhang, Zhiqiang Mei 2022 School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China;

Relative-Residual-Based Dynamic Schedule For Decoding Of Ldpc Codes, Fatang Chen, Hebin Li, Zhihao Zhang, Zhiqiang Mei

Journal of System Simulation

Abstract: In order to solve the problems of the oscillation phenomenon and greedy characteristics in the dynamic scheduling decoding algorithm for low-density parity-check (LDPC) codes, the relative-residual-based dynamic schedule (RRB-BP) algorithm is proposed based on variable-to-check residual belief propagation (VC-RBP) algorithm. The variable nodes are grouped, then the relative residual value of the message passed by the variable nodes to the check node is taken as a reference, and the node with the largest relative residual value is updated in priority to accelerate the decoding convergence speed. For variable nodes oscillating in the decoding process, the posterior LLR (log likelihood …


Energy-Efficient Scheduling Of Multi-Objective Flexible Job Shop Considering Interval Processing Time, Hongliang Zhang, Renman Ding, Gongjie Xu 2022 School of Management Science and Engineering, Anhui University of Technology, Ma’anshan 243032, China;

Energy-Efficient Scheduling Of Multi-Objective Flexible Job Shop Considering Interval Processing Time, Hongliang Zhang, Renman Ding, Gongjie Xu

Journal of System Simulation

Abstract: Based on the comprehensive consideration of economic indicators and environmental factors, the energy-efficient scheduling problem of multi-objective flexible job shop with uncertain processing time is studied. The interval number is used to describe uncertain processing time of the workpiece, and the optimization model for energy-efficient problem of interval flexible job shop scheduling is established to minimize the maximum interval completion time and total energy consumption. According to the domination relation of interval possibility degree, an effective interval multi-objective evolutionary algorithm is designed. The simulation experiments of the interval multi-objective evolutionary algorithm, SPEA-II and NSGA-II are carried out through 15 …


Particle Swarm Algorithm For Solving Emergency Material Dispatch Considering Urgency, Li Zhang, Huizhen Zhang, Dong Liu, Yuxin Lu 2022 School of Management, University of Shanghai for Science and Technology, Shanghai 200093, China;

Particle Swarm Algorithm For Solving Emergency Material Dispatch Considering Urgency, Li Zhang, Huizhen Zhang, Dong Liu, Yuxin Lu

Journal of System Simulation

Abstract: In the early stage of major public health events, medical supplies are rapidly consumed and severely insufficient. In order to distribute medical supplies in a reasonable and efficient manner, research on the distribution of emergency medical materials is carried out. The entropy method is introduced to determine the urgency of demand points, thus could give priority to the demand points with high urgency and make the distribution routing as short as possible on that basis to realize the construction of a split delivery and multi-objective emergency medical materials scheduling model based on different urgency of demand points. Meanwhile the …


Design Of Optical Compound Eye Simulation Software For Small Aircraft Applications, Qiming Qi, Ruigang Fu, Ping Wang, Min Wang, Hongqi Fan 2022 1.National University of Defense Technology, National Key Laboratory of Science and Technology on ATR, Changsha 410073, China;2.Unit 32139 of the Chinese PLA, Beijing 101200, China;

Design Of Optical Compound Eye Simulation Software For Small Aircraft Applications, Qiming Qi, Ruigang Fu, Ping Wang, Min Wang, Hongqi Fan

Journal of System Simulation

Abstract: Optical compound eye has the advantages of large field of view, multiple viewing angles and high resolution. With another advantage that it can conformal combine with small aircraft, optical compound eye has application value in reconnaissance and surveillance, target detection, image navigation and other aspects. An optical compound eye simulation software for small aircraft is designed for the current situation of long development period of optical compound eye design and high cost of flight test in practical applications. The software integrates compound eye imaging, aircraft simulation and data management, and each functional module is extensible. The simulation results show …


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