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Articles 91 - 120 of 1914
Full-Text Articles in Artificial Intelligence and Robotics
Simulation Of Incentive Mechanism Simulation On Reverse Supply Chain Of Waste Products Based On Dual Drive, Dongshi Sun, Danlan Xie, Guan Feng, Ji Yuan
Simulation Of Incentive Mechanism Simulation On Reverse Supply Chain Of Waste Products Based On Dual Drive, Dongshi Sun, Danlan Xie, Guan Feng, Ji Yuan
Journal of System Simulation
Abstract: In view of the current situation of coordination failure caused by different benefits of different entities in the waste reverse supply chain, based on system dynamics, a three-party evolutionary game model of residents, waste disposal institutions and production enterprises is constructed. Vensim simulation software is used to establish the stock-flow chart with the strategy selection probability as the horizontal variable. In the two cases of exogenous variable in constant and a time-trend, the simulation is carried out separately, and the strategy evolution path of the three parties is obtained without external interference. Through sensitivity analysis, the exogenous variables …
Effect Of New Titanium Alloy On Biomechanical Behavior Of Dental Implant, Jiwu Zhang, Qiguo Rong
Effect Of New Titanium Alloy On Biomechanical Behavior Of Dental Implant, Jiwu Zhang, Qiguo Rong
Journal of System Simulation
Abstract: Titanium alloy materials have excellent mechanical properties, chemical stability and biocompatibility, and have become the main raw materials for implants. However, the biomechanical compatibility of medical titanium alloys still needs to be improved in order to meet the long-term safety and functionality of patient's clinical treatment requirement. New medical titanium alloy materials with high strength and low modulus play an important role in reducing the loosening and shedding of implants caused by stress shielding. The effects of new medical titanium alloy materials and traditional medical titanium alloy materials on implant structure and stress distribution of jaw are compared and …
Research On Real-Time Simulation Method Of Bi-Sar Echo In Time-Varying Sea Scene, Guijie Diao, Ni Hong, Zhe Liu, Li Yang
Research On Real-Time Simulation Method Of Bi-Sar Echo In Time-Varying Sea Scene, Guijie Diao, Ni Hong, Zhe Liu, Li Yang
Journal of System Simulation
Abstract: Based on bistatic scattering mechanism and the geometric relationship of bistatic synthetic aperture radar (Bi-SAR), a real-time simulation method of Bi-SAR radio frequency echo in time-varying sea scene is proposed. For the couple scattering in time-varying sea scene, a Bi-SAR echo signal model is established on the basis of multipath scattering model. The Bi-SAR system response function for time-varying sea target is calculated in real-time, using high performance computing technology, high-capacity real-time access technology and full-switching system designing. The simulation results show the effectiveness of the method.
Bert Efficacy On Scientific And Medical Datasets: A Systematic Literature Review, Clayton Cohn
Bert Efficacy On Scientific And Medical Datasets: A Systematic Literature Review, Clayton Cohn
College of Computing and Digital Media Dissertations
Bidirectional Encoder Representations from Transformers (BERT) [Devlin et al., 2018] has been shown to be effective at modeling a multitude of datasets across a wide variety of Natural Language Processing (NLP) tasks; however, little research has been done regarding BERT’s effectiveness at modeling domain-specific datasets. Specifically, scientific and medical datasets present a particularly difficult challenge in NLP, as these types of corpora are often rife with technical jargon that is largely absent from the canonical corpora that BERT and other transfer learning models were originally trained on. This thesis is a Systematic Literature Review (SLR) of twenty-seven studies that were …
A Pmbldc Motor Measurement And Control System Available For Zynq Hardware-In-The-Loop Simulation, Zhiguo Zhou, Jiaen Sun, Jiabao Yu, Xuehua Zhou
A Pmbldc Motor Measurement And Control System Available For Zynq Hardware-In-The-Loop Simulation, Zhiguo Zhou, Jiaen Sun, Jiabao Yu, Xuehua Zhou
Journal of System Simulation
Abstract: In order to solve the modeling of permanent magnet brushless dc(PMBLDC) motor, it is difficult to modify the control algorithm, inconvenient to add and remove the closed loop, and has poor real-time measurement and control capability. Based on hall sensor position detection algorithm and PID control algorithm, combined with piecewise linear method to generate PWM waveform, Simulink graphical modeling platform is used, and a new closed-loop measurement and control method is proposed. A sudden load and sudden speed simulation are carried out to verify the established PMBLDC motor measurement and control system. The simulation results show that the system …
Integrating Deep Learning And Augmented Reality To Enhance Situational Awareness In Firefighting Environments, Manish Bhattarai
Integrating Deep Learning And Augmented Reality To Enhance Situational Awareness In Firefighting Environments, Manish Bhattarai
Electrical and Computer Engineering ETDs
We present a new four-pronged approach to build firefighter's situational awareness for the first time in the literature. We construct a series of deep learning frameworks built on top of one another to enhance the safety, efficiency, and successful completion of rescue missions conducted by firefighters in emergency first response settings. First, we used a deep Convolutional Neural Network (CNN) system to classify and identify objects of interest from thermal imagery in real-time. Next, we extended this CNN framework for object detection, tracking, segmentation with a Mask RCNN framework, and scene description with a multimodal natural language processing(NLP) framework. Third, …
Deep Learning With Physics Informed Neural Networks For The Airborne Spread Of Covid-19 In Enclosed Spaces, Udbhav Muthakana, Padmanabhan Seshaiyer, Maziar Raissi, Long Nguyen
Deep Learning With Physics Informed Neural Networks For The Airborne Spread Of Covid-19 In Enclosed Spaces, Udbhav Muthakana, Padmanabhan Seshaiyer, Maziar Raissi, Long Nguyen
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Multimodal Data Fusion And Attack Detection In Recommender Systems, Mehmet Aktukmak
Multimodal Data Fusion And Attack Detection In Recommender Systems, Mehmet Aktukmak
USF Tampa Graduate Theses and Dissertations
The commercial platforms that use recommender systems can collect relevant information to produce useful recommendations to the platform users. However, these sources usually contain missing values, imbalanced and heterogeneous data, and noisy observations. Such characteristics render the process of exploiting the information nontrivial, as one should carefully address them during the data fusion process. In addition to the degenerative characteristics, some entries can be fake, i.e., they can be the outcomes of malicious intents to manipulate the system. These entries should be eliminated before incorporation to any recommendation task. Detecting such malicious attacks quickly and accurately and then mitigating them …
Extending The Functional Subnetwork Approach To A Generalized Linear Integrate-And-Fire Neuron Model, Nicholas Szczecinski, Roger Quinn, Alexander J. Hunt
Extending The Functional Subnetwork Approach To A Generalized Linear Integrate-And-Fire Neuron Model, Nicholas Szczecinski, Roger Quinn, Alexander J. Hunt
Mechanical and Materials Engineering Faculty Publications and Presentations
Engineering neural networks to perform specific tasks often represents a monumental challenge in determining network architecture and parameter values. In this work, we extend our previously-developed method for tuning networks of non-spiking neurons, the “Functional subnetwork approach” (FSA), to the tuning of networks composed of spiking neurons. This extension enables the direct assembly and tuning of networks of spiking neurons and synapses based on the network’s intended function, without the use of global optimization ormachine learning. To extend the FSA, we show that the dynamics of a generalized linear integrate and fire (GLIF) neuronmodel have fundamental similarities to those of …
Law Library Blog (November 2020): Legal Beagle's Blog Archive, Roger Williams University School Of Law
Law Library Blog (November 2020): Legal Beagle's Blog Archive, Roger Williams University School Of Law
Law Library Newsletters/Blog
No abstract provided.
Bist: Bi-Directional Spatio-Temporal Reasoning For Video-Grounded Dialogues, Hung Le, Doyen Sahoo, Nancy F. Chen, Steven C. H. Hoi
Bist: Bi-Directional Spatio-Temporal Reasoning For Video-Grounded Dialogues, Hung Le, Doyen Sahoo, Nancy F. Chen, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
Video-grounded dialogues are very challenging due to (i) the complexity of videos which contain both spatial and temporal variations, and (ii) the complexity of user utterances which query different segments and/or different objects in videos over multiple dialogue turns. However, existing approaches to video-grounded dialogues often focus on superficial temporal-level visual cues, but neglect more fine-grained spatial signals from videos. To address this drawback, we propose Bi-directional Spatio-Temporal Learning (BiST), a vision-language neural framework for high-resolution queries in videos based on textual cues. Specifically, our approach not only exploits both spatial and temporal-level information, but also learns dynamic information diffusion …
Uniconv: A Unified Conversational Neural Architecture For Multi-Domain Task-Oriented Dialogues, Hung Le, Doyen Sahoo, Chenghao Liu, Nancy F. Chen, Steven C. H. Hoi
Uniconv: A Unified Conversational Neural Architecture For Multi-Domain Task-Oriented Dialogues, Hung Le, Doyen Sahoo, Chenghao Liu, Nancy F. Chen, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
Building an end-to-end conversational agent for multi-domain task-oriented dialogues has been an open challenge for two main reasons. First, tracking dialogue states of multiple domains is non-trivial as the dialogue agent must obtain complete states from all relevant domains, some of which might have shared slots among domains as well as unique slots specifically for one domain only. Second, the dialogue agent must also process various types of information across domains, including dialogue context, dialogue states, and database, to generate natural responses to users. Unlike the existing approaches that are often designed to train each module separately, we propose “UniConv" …
Machine Learning Integrated Design For Additive Manufacturing, Jingchao Jiang, Yi Xiong, Zhiyuan Zhang, David W. Rosen
Machine Learning Integrated Design For Additive Manufacturing, Jingchao Jiang, Yi Xiong, Zhiyuan Zhang, David W. Rosen
Research Collection School Of Computing and Information Systems
For improving manufacturing efficiency and minimizing costs, design for additive manufacturing (AM) has been accordingly proposed. The existing design for AM methods are mainly surrogate model based. Due to the increasingly available data nowadays, machine learning (ML) has been applied to medical diagnosis, image processing, prediction, classification, learning association, etc. A variety of studies have also been carried out to use machine learning for optimizing the process parameters of AM with corresponding objectives. In this paper, a ML integrated design for AM framework is proposed, which takes advantage of ML that can learn the complex relationships between the design and …
Global Context Aware Convolutions For 3d Point Cloud Understanding, Zhiyuan Zhang, Binh-Son Hua, Wei Chen, Yibin Tian, Sai-Kit Yeung
Global Context Aware Convolutions For 3d Point Cloud Understanding, Zhiyuan Zhang, Binh-Son Hua, Wei Chen, Yibin Tian, Sai-Kit Yeung
Research Collection School Of Computing and Information Systems
Recent advances in deep learning for 3D point clouds have shown great promises in scene understanding tasks thanks to the introduction of convolution operators to consume 3D point clouds directly in a neural network. Point cloud data, however, could have arbitrary rotations, especially those acquired from 3D scanning. Recent works show that it is possible to design point cloud convolutions with rotation invariance property, but such methods generally do not perform as well as translation-invariant only convolution. We found that a key reason is that compared to point coordinates, rotation-invariant features consumed by point cloud convolution are not as distinctive. …
Communicating Uncertain Information From Deep Learning Models In Human Machine Teams, Harishankar V. Subramanian, Casey I. Canfield, Daniel Burton Shank, Luke Andrews, Cihan H. Dagli
Communicating Uncertain Information From Deep Learning Models In Human Machine Teams, Harishankar V. Subramanian, Casey I. Canfield, Daniel Burton Shank, Luke Andrews, Cihan H. Dagli
Engineering Management and Systems Engineering Faculty Research & Creative Works
The role of human-machine teams in society is increasing, as big data and computing power explode. One popular approach to AI is deep learning, which is useful for classification, feature identification, and predictive modeling. However, deep learning models often suffer from inadequate transparency and poor explainability. One aspect of human systems integration is the design of interfaces that support human decision-making. AI models have multiple types of uncertainty embedded, which may be difficult for users to understand. Humans that use these tools need to understand how much they should trust the AI. This study evaluates one simple approach for communicating …
Finite-Time State Estimation For An Inverted Pendulum Under Input-Multiplicative Uncertainty, Sergey V. Drakunov, William Mackunis, Anu Kossery Jayaprakash, Krishna Bhavithavya Kidambi, Mahmut Reyhanoglu
Finite-Time State Estimation For An Inverted Pendulum Under Input-Multiplicative Uncertainty, Sergey V. Drakunov, William Mackunis, Anu Kossery Jayaprakash, Krishna Bhavithavya Kidambi, Mahmut Reyhanoglu
Publications
A sliding mode observer is presented, which is rigorously proven to achieve finite-time state estimation of a dual-parallel underactuated (i.e., single-input multi-output) cart inverted pendulum system in the presence of parametric uncertainty. A salient feature of the proposed sliding mode observer design is that a rigorous analysis is provided, which proves finite-time estimation of the complete system state in the presence of input-multiplicative parametric uncertainty. The performance of the proposed observer design is demonstrated through numerical case studies using both sliding mode control (SMC)- and linear quadratic regulator (LQR)-based closed-loop control systems. The main contribution presented here is the rigorous …
Espade: An Efficient And Semantically Secure Shortest Path Discovery For Outsourced Location-Based Services, Bharath K. Samanthula, Divyadharshini Karthikeyan, Boxiang Dong, K. Anitha Kumari
Espade: An Efficient And Semantically Secure Shortest Path Discovery For Outsourced Location-Based Services, Bharath K. Samanthula, Divyadharshini Karthikeyan, Boxiang Dong, K. Anitha Kumari
Department of Computer Science Faculty Scholarship and Creative Works
With the rapid growth of smart devices and technological advancements in tracking geospatial data, the demand for Location-Based Services (LBS) is facing a constant rise in several domains, including military, healthcare and transportation. It is a natural step to migrate LBS to a cloud environment to achieve on-demand scalability and increased resiliency. Nonetheless, outsourcing sensitive location data to a third-party cloud provider raises a host of privacy concerns as the data owners have reduced visibility and control over the outsourced data. In this paper, we consider outsourced LBS where users want to retrieve map directions without disclosing their location information. …
Research On Optimal Configuration Design Method Of Stewart Platform, Xuwei Fan, Lili Yang, Cheng Yu, Xiaoning Zhou, Yexin Zhang
Research On Optimal Configuration Design Method Of Stewart Platform, Xuwei Fan, Lili Yang, Cheng Yu, Xiaoning Zhou, Yexin Zhang
Journal of System Simulation
Abstract: Based on the structural singularity and configuration singularity of parallel mechanism, a safety mechanism design scheme of the Stewart platform is proposed to improve the workspace efficiency and engineering practicability. Taking the Stewart platform without any particularity as the research object, and considering the singular constraints of the structure, a dexterity index is proposed to achieve the optimization of the structural parameters. Analyzing and constructing the kinematics model of the Stewart platform, analyzing the singularities of the configuration bifurcations of 16 typical extreme poses, a secure workspace verification algorithm is proposed to make the whole workspace free of singularity. …
Research On Adaptive Routing Algorithm For Wireless Weak-Connection Network, Hua Xiang, Hongjuan Yao, Wang Hai, Wang Zhao, Jietao Zhang, Lili Shu
Research On Adaptive Routing Algorithm For Wireless Weak-Connection Network, Hua Xiang, Hongjuan Yao, Wang Hai, Wang Zhao, Jietao Zhang, Lili Shu
Journal of System Simulation
Abstract: The wireless weak-connected network has the characteristics of long delay, high dynamic topology, and unstable links. With the lack of continuity from the source end to the destination end of network connection, in order to solve the problem of communication difficulty, the intelligence and adaptability of Physarum polycephalum are introduced, and the adaptive wireless weak-connected network routing algorithm is proposed. A wireless weak-connected network model is build and the mathematical relationships of link capacity is deduced. The next-hop selection strategy and optimal routing strategy is designed to achieve the best-effort delivery of data in wireless weak-connected network environmrnt. Simulation …
Visual Feedback Fuzzy Control For A Robot Manipulator Based On Svr Learning, Xianxia Zhang, Jinqiang Zhang, Zhiyuan Li, Shiwei Ma, Banghua Yang
Visual Feedback Fuzzy Control For A Robot Manipulator Based On Svr Learning, Xianxia Zhang, Jinqiang Zhang, Zhiyuan Li, Shiwei Ma, Banghua Yang
Journal of System Simulation
Abstract: A fuzzy controller based on SVR learning is proposed for uncalibrated robot visual servoing. In this paper, a fuzzy controller is used to directly construct the nonlinear mapping between image features and robot joint motion. The fuzzy basis function of the fuzzy controller is taken as the kernel function of an SVR and the equivalent relationship between the SVR and the fuzzy controller is established. The learned support vector from the SVR is used as the rule of the fuzzy controller. Since all rules are learned from the data, there is no need to manually design the rules. …
Gru-Based Car-Following Behavior Simulation Model, Fei Rong, Liu Fang, Xie Guo, Hei Xinhong, Shasha Li, Hu Bo
Gru-Based Car-Following Behavior Simulation Model, Fei Rong, Liu Fang, Xie Guo, Hei Xinhong, Shasha Li, Hu Bo
Journal of System Simulation
Abstract: The accuracy of acceleration prediction can be effectively improved by the driver's memory in car-following behavior. A new car-following model based on the General Motors (GM) and the gate control unit (GRU) is proposed. The car-following data between small vehicles with similar driving behavior are obtained by data preprocessing. The established model is calibrated by the car-following data, and the optimal parameters and structure of the model are determined. According to car-following characteristics, the effectiveness of model is verified by simulation. It is confirmed that the model has high robustness and improved simulation accuracy comparing with the traditional models.
Estimation Of Space-Time Of Urban Building Population Based On Mobile Phone Big Data, Hu Yang, Xiaoyong Zhang, Xiao Di
Estimation Of Space-Time Of Urban Building Population Based On Mobile Phone Big Data, Hu Yang, Xiaoyong Zhang, Xiao Di
Journal of System Simulation
Abstract: With the acceleration of the urbanization process, mastering the population distribution on a fine scale is of great significance for urban disaster assessment, emergency response management and public resource allocation. The rapid development of the Internet and the popularity of smartphones have prompted mobile phones to become the sensors of human activity. A method of urban building population estimation based on mobile phone big data is proposed. The method analyzes the crowd activity law of buildings with different functions based on mobile phone positioning big data in typical areas, calculates the population capacity of different functional buildings, and …
Simulation Research On Optimization Of Agv Charging Strategy For Automated Terminal, Danlan Xie, Guo Di, Ji Yuan, Zhipeng Gao
Simulation Research On Optimization Of Agv Charging Strategy For Automated Terminal, Danlan Xie, Guo Di, Ji Yuan, Zhipeng Gao
Journal of System Simulation
Abstract: As the automated container terminal is the development trend of terminal, AGV (automated guided vehicle) becomes the most widely used horizontal transportation tool and it is important to make its reasonable charging strategy. Aiming at the shortcomings of the current AGV, a charging strategy of offline charging being primary and online charging being auxiliary is proposed. In order to solve the problem of location selection of online charging station, a quick method of selecting effective stations by using heat zone map is proposed. Through a large number of simulation experiments using this strategy, the fact that the number …
Global Optimization Method Based On Consensus Particle Swarm Optimization, Zhanwen Lu, Xingong Cheng, Yongfeng Zhang
Global Optimization Method Based On Consensus Particle Swarm Optimization, Zhanwen Lu, Xingong Cheng, Yongfeng Zhang
Journal of System Simulation
Abstract: According to the characteristics of particle swarm optimization (PSO) and efficient global optimization algorithm (EGO), a global black box optimization algorithm based on consensus particle swarm optimization and local surrogate model (CPSO-LSM) is proposed. The algorithm fixes the period of the PSO algorithm to group the particles and stops after the particles reach a consensus. The high-quality sub-regions around each group of particles are used as the modeling area of the surrogate model, and the high-quality optimal solution or global optimal solution is obtained by comparing the optimal values of each region. It can not only avoid the complex …
Natural Computing Method Based On Lle Dimension Reduction, Luyao Zhang, Weidong Ji, Cheng Hao
Natural Computing Method Based On Lle Dimension Reduction, Luyao Zhang, Weidong Ji, Cheng Hao
Journal of System Simulation
Abstract: In the natural computing method, the appearance of high-dimensional problem can make some existing optimization algorithms avoid falling into local optimum, but it makes the performance of the algorithm worse and the running time longer. On the basis of traditional natural calculation method, a natural calculation method based on LLE(Local Linear Embedding) algorithm is proposed, which analyzes the value of neighbor particle k and dimension d, and makes the algorithm get better optimization effect after dimension reduction. In the process, a small bias s is added to the data after dimension reduction to increase the diversity of …
Research On Distribution Line Identification And Simulation Based On Sequence Impedance Method, Keyan Liu, Weijie Dong, Xueshun Ye, Muke Bai, Huaitian Zhang
Research On Distribution Line Identification And Simulation Based On Sequence Impedance Method, Keyan Liu, Weijie Dong, Xueshun Ye, Muke Bai, Huaitian Zhang
Journal of System Simulation
Abstract: The field fault test of distribution network cannot be repeated frequently, a line parameter identification and fault waveform reproduction method based on sequence impedance method is proposed to build the line sequence resistance model, and the π type equivalent lines are constructed. Based on the data of each node obtained in the field test process, the positive sequence impedance and zero sequence impedance parameters of π type equivalent circuits of all line sections are obtained by using the principle of symmetrical sequence components, and the digital model of the real lines in the field is established. The simulation results …
Research On Fuzzy Flexible Job Shop Scheduling Problem Based On Hybrid Qpso, Junxuan Li, Wang Yan, Zhicheng Ji
Research On Fuzzy Flexible Job Shop Scheduling Problem Based On Hybrid Qpso, Junxuan Li, Wang Yan, Zhicheng Ji
Journal of System Simulation
Abstract: To solve the flexible job shop scheduling problem of uncertain processing time, triangular fuzzy numbers are used to characterize the relevant time parameters and a Hybrid Quantum Particle Swarm Optimization (HQPSO) is proposed. On the basis of making full use of the global search capability of Quantum Particle Swarm Optimization, the search efficiency is increased by designing a boundary repair strategy and a cooperative update strategy. Meanwhile, the cross-operator and path relinking technique are used to in the operation sequence mapped by the excellent particles, which makes up the disadvantages of the insufficient ability of deeply exploration of …
Adaptive Control Method Of High Proportion Distributed Generation Connected To Distribution Network, Weijie Dong, Keyan Liu, Yilong Wang, Xiaozhong Li, Yang Hao
Adaptive Control Method Of High Proportion Distributed Generation Connected To Distribution Network, Weijie Dong, Keyan Liu, Yilong Wang, Xiaozhong Li, Yang Hao
Journal of System Simulation
Abstract: Focus on the instability of the reactive power output precision caused by the voltage drop and loss of DG lines being switched to grid and the low output frequency and voltage caused by power deficiency of DG islanding, an improved droop control strategy is proposed to ensure the running stability of Active Distribution Network during DG connecting to network. The DG model applies the feedback regulation of f-U droop output power and voltage drop compensator. The control system is applied to the quasi-synchronization grid-connected model, island mode and the modes switching process of an active distribution network's domain transient …
Optimization Of Shore Bridge Driver Scheduling Strategy Considering Influence Of Illumination, Tiexin Wang, Haihong Yu, Danlan Xie, Yibin Wang
Optimization Of Shore Bridge Driver Scheduling Strategy Considering Influence Of Illumination, Tiexin Wang, Haihong Yu, Danlan Xie, Yibin Wang
Journal of System Simulation
Abstract: The luminous environment has an important effect on the efficiency of quay crane drivers' work. Aiming at the quay crane drivers' shift arrangement under the changing illumination intensity, the theoretical model of illumination influencing efficiency and the 3D simulation model of port operation are established. The influence of different lighting conditions on quay crane drivers' work is analyzed to find the optimal scheduling strategy. By comparing four different scheduling strategies, the optimal 6h interval scheduling is obtained, which increases the working efficiency by about 14% compared with the existing scheduling methods. It shows that when the total working …
Cascading Failure Analysis Of Equipment Support Network Based On Sirv Virus Propagation Theory, Zhang Qiang, Junhai Cao, Tailiang Song, Haidong Du, Chuang Zhang
Cascading Failure Analysis Of Equipment Support Network Based On Sirv Virus Propagation Theory, Zhang Qiang, Junhai Cao, Tailiang Song, Haidong Du, Chuang Zhang
Journal of System Simulation
Abstract: According to the complexity phenomenon of equipment support network being attacked by the enemy, the similarity between network cascading process and virus propagation process is compared and analyzed. On the basis of the existing load capacity cascading failure model, the process of virus immune propagation is integrated, four different states of support nodes are defined, and the cascade transmission model of equipment support network is constructed, which can better reproduce the real situation of our support organization being attacked by the enemy and public opinion. The simulation and comparison shows that when the defense resources are limited and the …