Urban Uav Path Planning Based On Improved Beetle Search Algorithm,
2023
School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China; Yunnan Provincial Key Laboratory of Computer Science, Kunming University of Science and Technology, Kunming 650500, China
Urban Uav Path Planning Based On Improved Beetle Search Algorithm, Qingqing Yang, Minyi Deng, Yi Peng
Journal of System Simulation
Abstract: An improved SABAS is proposed to improve the safety and path smoothing of UAV missions in urban multi-obstacle environments and to obtain the shortest path. The algorithm no longer completely depends on the difference of odor concentration between the left and the right tentacles of beetle when exploring the path for position update. Instead, it makes full use of the strong searching ability of BAS algorithm, and introduces the annealing algorithm to add the neighborhood position solution of the next position, and finally selects the next best position from the neighborhood position solution. Metropolis criterion of annealing algorithm is …
Task Scheduling For Internet Of Vehicles Based On Deep Reinforcement Learning In Edge Computing,
2023
School of Electronic and Electrical Engineering, Shanghai University of Engineering Science, Shanghai 201620, China
Task Scheduling For Internet Of Vehicles Based On Deep Reinforcement Learning In Edge Computing, Xiang Ju, Shengchao Su, Chaojie Xu, Beibei He
Journal of System Simulation
Abstract: Aiming at the offloading and execution of delay-constrained computing tasks for internet of vehicles in edge computing, a task scheduling method based on deep reinforcement learning is proposed. In multi-edge server scenario, a software-defined network-aided internet of vehicles task offloading system is built. On this basis, the task scheduling model of vehicle computation offloading is given. According to the characteristics of task scheduling, a scheduling method based on an improved pointer network is designed. Considering the complexity of task scheduling and computing resource allocation, the deep reinforcement learning algorithm is used to train the pointer network. The vehicle offloading …
Airport Operational Efficiency Evaluation Based On Combined Weighting-Topsis Model,
2023
The 28th Research Institute of China Electronics Technology Group Corporation, Nanjing 210007, China; State Key Laboratory of Air Traffic Management System, Nanjing 210007, China
Airport Operational Efficiency Evaluation Based On Combined Weighting-Topsis Model, Jie Hu, Fan Bao
Journal of System Simulation
Abstract: In order to improve the scientificity and comprehensiveness of the airport operational efficiency evaluation, a new method based on the combined weighting-TOPSIS model is proposed. From 4 dimensions of stand operational efficiency, passenger boarding efficiency, aircraft taxiing efficiency, and coordination efficiency, a new airport operational efficiency evaluation system consisting of 11 indicators, such as flight approach rate, corridor bridge turnover rate, stand change ratio, etc., are constructed. G1 method and entropy weight method are implemented respectively to calculate the subjective and objective weights of the evaluation indicators, and the combined weights are calculated by minimizing the deviation of subjective …
Research On Network Public Opinion Propagation Model Of Major Epidemics Under Cross-Infection Of Double Emotions,
2023
School of Economics and Management, Yanshan University, Qinhuangdao 066004, China; Center for Internet Plus and Industry Development, Yanshan University, Qinhuangdao 066004, China; Research Center of Regional Economic Development, Yanshan University, Qinhuangdao 066004, China
Research On Network Public Opinion Propagation Model Of Major Epidemics Under Cross-Infection Of Double Emotions, Yaming Zhang, Yanyuan Su, Guiru Zhao, Xiaoyu Guo
Journal of System Simulation
Abstract: Major epidemics provoke a variety of netizens' emotions. To some degree, the interaction of netizens' intense emotions determine the development direction of public opinion. Considering the complexity and dual emotional contagion, the impact of emotional factors in network public opinion is quantified to three dimensions indicators, emotional enhancement, differences and conversion rates. SIPINR public opinion propagation model is constructed. The equilibrium points and the transmission threshold are estimated and the stability is proved. The law of network public opinion propagation during major epidemics is revealed through numerical simulation. The results show that the dual emotional contagion would lead to …
Automatic Target Recognition Of Substation 3d Scene For Digital Twin,
2023
Anhui Electric Power Engineering Supervision Co. , Ltd. , Hefei 230071, China
Automatic Target Recognition Of Substation 3d Scene For Digital Twin, Qian Tu, Jun Li, Dongliang Fan, Qi Kong, Jie Shen
Journal of System Simulation
Abstract: In order to improve the accuracy of automatic target recognition and promote the effect on substation operation and maintenance, automatic target recognition of substation 3D scene for digital twin is proposed. The automatic target recognition model for the three dimensional scene of the substation is constructed. The perception module of the model is used to collect the real-time status data of substation, and the communication module is used to transmit the data to digital twin modules. This module, based on the received data information, realizes the deep fusion and panoramic mapping of substation information through the knowledge base constructed …
Simulation On High-Speed Train Carriage Evacuation Considering Passengers Moving To Adjacent Carriages,
2023
School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 611756, China; National Engineering Laboratory of Integrated Transportation Big Data Application Technology, Southwest Jiaotong University, Chengdu 611756, China
Simulation On High-Speed Train Carriage Evacuation Considering Passengers Moving To Adjacent Carriages, Zuoan Hu, Tian Zeng, Yidong Wei, Yi Ma
Journal of System Simulation
Abstract: To study the influence of passengers moving to adjacent carriages on high-speed train carriages' evacuation, a cellular automata model considering export selection is established. Taking the CR400BF second-class carriage as the research object, some analytical indexes such as evacuation efficiency, number of conflicts and the congestion degree are used to study the effect of passengers moving to adjacent carriages on carriage evacuation, and the passenger seat distribution, the number of passengers transferred from adjacent carriages and the opening door modes of adjacent carriages are discussed. The simulation results show that the discretized seat distribution reduces the times of conflicts …
Application Of Improved Path Tracking Algorithm In Robot Slam,
2023
School of Information Science and Technology, Qingdao University of Science and Technology, Qingdao 266061, China
Application Of Improved Path Tracking Algorithm In Robot Slam, Qian Li, Ye Tao, Hui Li
Journal of System Simulation
Abstract: Mapping is an important part of automated logistics. At present, SLAM is widely used. However, in large-scale scenes, errors are accumulated because robots often repeatedly measure and scan the region edge, which makes it impossible to quickly build a high-precision and complete map. An autonomous mapping method based on auxiliary path tracking is proposed, in which the given initial sketch is grid denoised and the auxiliary path is fitted and improved by multi segment cubic polynomial. The improved pure pursuit algorithm is used to guide the robot to build the map and improve the total distance and time of …
Modeling And Simulation On Production Logistics Of Intelligent Workshop Manufacturing System Based On Efsm,
2023
Nanjing University of Science and Technology, Nanjing 210094, China; 2. Beijing Simulation Center, Beijing 100854, China
Modeling And Simulation On Production Logistics Of Intelligent Workshop Manufacturing System Based On Efsm, Liuzhen Li, Chao Jin, Tingyu Lin, Yaoqin Zhu
Journal of System Simulation
Abstract: The production logistics mode of manufacturing industry is developing rapidly, on which the modeling and simulation can provide the decision support for the design, analysis and transformation of manufacturing system. A description of the entity elements in intelligent workshop manufacturing system is given according to the classification of "human machine material environment rule". A production and logistics componentized EFSM model is created on the basis of EFSM and componentized modeling ideas. The modeling process for multi-job production in smart shop and the component model instantiation methodology are elaborated. The simulation running through the automatic conversion of EFSM-DEVS model and …
Research On 3d Object Detection Method With Cross-Module Attention,
2023
Academy of Army Armored Force, Beijing 100072, China
Research On 3d Object Detection Method With Cross-Module Attention, Renjie Xu, Xiaoming Zhang, Chen Wang, Peng Wu
Journal of System Simulation
Abstract: To address the issue of feature loss that occurs during the extraction and transmission of target features in 3D object detection tasks using point cloud data, this study proposes an object detection method based on cross-module attention. This method incorporates a channel attention module and a spatial attention module to enhance the crucial feature information. Through feature transformation, the features from different stages of the attention module are connected to mitigate the loss of features during the extraction and transmission process. To tackle the problem of inadequate detection performance in target detection networks for objects of different scales, a …
Robotic Arms For Microgravity Manufacturing,
2023
Kennesaw State University
Robotic Arms For Microgravity Manufacturing, Connor Talley, Joshua Diamond, Mickael Bah
Senior Design Project For Engineers
There is a need to reduce manufacturing cost in space to avoid sending earth manufactured parts that could suffer damage during launch. The proposed idea consists of a dual robotic arm system attached on a precision gantry setup. The team developed an innovative design that is flexible and efficient for different assemblies, improving space manufacturing. With its two specialized robotic arms, our system maximizes versatility by catering to a wide variety of applications from manufacturing to assembly. The dual arms made of Al 7075 coupled with the gantry provides stability and performance in microgravity environments.
Bitcoin's Technical Foundation And Its Potential For A Decentralized And Environmentally Friendly Future,
2023
University of Texas at El Paso
Bitcoin's Technical Foundation And Its Potential For A Decentralized And Environmentally Friendly Future, Iqtiar Md Siddique
Open Access Theses & Dissertations
This research examines a systematic analysis of Bitcoin, employing a Coefficient of Variation (CV) approach to gauge its degree of decentralization. Bitcoin, an innovative decentralized digital currency, has received much attention for its potential to revolutionize traditional financial systems. This study employs the Coefficient of Variation (CV) to acquire insights into the wealth distribution and concentration among Bitcoin users. This research demonstrates how decentralized the network of Bitcoin is. The methodology uses real data on Bitcoin addresses and their holdings to compute the Coefficient of Variation (CV). This approach provides valuable insights into the ongoing discourse surrounding Bitcoin's decentralization, offering …
Development Of A Machine Learning System For Irrigation Decision Support With Disparate Data Streams,
2023
University of Nebraska-Lincoln
Development Of A Machine Learning System For Irrigation Decision Support With Disparate Data Streams, Eric Wilkening
Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research
In recent years, advancements in irrigation technologies have led to increased efficiency in irrigation applications, encompassing the adoption of practices that utilize data-driven irrigation scheduling and leveraging variable rate irrigation (VRI). These technological improvements have the potential to reduce water withdrawals and diversions from both groundwater and surface water sources. However, it is vital to recognize that improved application efficiency does not necessarily equate to increased water availability for future or downstream use. This is particularly crucial in the context of consumptive water use, which refers to water consumed and not returned to the local or sub-regional watershed, representing a …
Enhancing Accident Investigation Using Traffic Cctv Footage,
2023
California State University, San Bernardino
Enhancing Accident Investigation Using Traffic Cctv Footage, Aksharapriya Peddi
Electronic Theses, Projects, and Dissertations
This Culminating Experience Project investigated how the densenet-161 model will perform on accident severity prediction compared to proposed methods. The research questions are: (Q1) What is the impact of usage of augmentation techniques on imbalanced datasets? (Q2) How will the hyper parameter tuning affect the model performance? (Q3) How effective is the proposed model compared to existing work? The findings are: Q1. The effectiveness of our model depends on the implementation of augmentation techniques that pay attention to handling imbalanced datasets. Our dataset poses a challenge due to distribution of classes in terms of accident severity. To address this challenge …
Convolution And Autoencoders Applied To Nonlinear Differential Equations,
2023
East Tennessee State University
Convolution And Autoencoders Applied To Nonlinear Differential Equations, Noah Borquaye
Electronic Theses and Dissertations
Autoencoders, a type of artificial neural network, have gained recognition by researchers in various fields, especially machine learning due to their vast applications in data representations from inputs. Recently researchers have explored the possibility to extend the application of autoencoders to solve nonlinear differential equations. Algorithms and methods employed in an autoencoder framework include sparse identification of nonlinear dynamics (SINDy), dynamic mode decomposition (DMD), Koopman operator theory and singular value decomposition (SVD). These approaches use matrix multiplication to represent linear transformation. However, machine learning algorithms often use convolution to represent linear transformations. In our work, we modify these approaches to …
Classification Of Large Scale Fish Dataset By Deep Neural Networks,
2023
California State University, San Bernardino
Classification Of Large Scale Fish Dataset By Deep Neural Networks, Priyanka Adapa
Electronic Theses, Projects, and Dissertations
The development of robust and efficient fish classification systems has become essential to preventing the rapid depletion of aquatic resources and building conservation strategies. A deep learning approach is proposed here for the automated classification of fish species from underwater images. The proposed methodology leverages state-of-the-art deep neural networks by applying the compact convolutional transformer (CCT) architecture, which is famous for faster training and lower computational cost. In CCT, data augmentation techniques are employed to enhance the variability of the training data, reducing overfitting and improving generalization. The preliminary outcomes of our proposed method demonstrate a promising accuracy level of …
Application Of Virtual-Real Simulation In Military Field,
2023
College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410000, China
Application Of Virtual-Real Simulation In Military Field, Ziquan Mao, Jialong Gao, Jianxing Gong, Quan Liu
Journal of System Simulation
Abstract: The definition and content of the virtual-real simulation are presented. According to different technical ideas, the development status and existing problems of virtual-real simulation are summarized from three aspects of digital twin, live-virtual-constructive (LVC) simulation, and parallel system. The similarities and differences, as well as the advantages and disadvantages of the three methods are analyzed and compared, and their main application fields are discussed. In order to deal with difficulties encountered in military training, operational tests, equipment development, and equipment maintenance, a solution based on virtual-real simulation is proposed by means of theoretical guidance, case comparison, and transfer and …
Image Semantic Segmentation Algorithm Based On Improved Deeplabv3+,
2023
Liaoning General Aviation Academy, Shenyang Aerospace University, Shenyang 110034, China; College of Electronic Information Engineering, Shenyang Aerospace University, Shenyang 110034, China
Image Semantic Segmentation Algorithm Based On Improved Deeplabv3+, Weiping Zhao, Yu Chen, Song Xiang, Yuanqiang Liu, Chaoyue Wang
Journal of System Simulation
Abstract: Mainstream image semantic segmentation networks currently face problems such as incorrec segmentation, discontinuous segmentation, and high model complexity, which cannot be flexibly and efficiently deployed in practical scenarios. To this end, an image semantic segmentation network that optimizes the DeepLabv3+ model is designed by comprehensively considering the network parameters, prediction time, and accuracy. The lightweight EfficientNetv2 is adopted to extract backbone network features and improve parameter utilization. In the atrous spatial pyramid pooling module, the mixed strip pooling is utilized to replace the global average pooling, and a depthwise separable dilated convolution is introduced to reduce parameters and improve …
Intercell Dynamic Scheduling Method Based On Deep Reinforcement Learning,
2023
University of Shanghai for Science and Technology, Shanghai 200093, China
Intercell Dynamic Scheduling Method Based On Deep Reinforcement Learning, Jing Ni, Mengke Ma
Journal of System Simulation
Abstract: In order to solve the intercell scheduling problem of dynamic arrival of machining tasks and realize adaptive scheduling in the complex and changeable environment of the intelligent factory, a scheduling method based on a deep Q network is proposed. A complex network with cells as nodes and workpiece intercell machining path as directed edges is constructed, and the degree value is introduced to define the state space with intercell scheduling characteristics. A compound scheduling rule composed of a workpiece layer, unit layer, and machine layer is designed, and hierarchical optimization makes the scheduling scheme more global. Since double deep …
Analysis Of Autonomous Aerial Refueling Capability Requirements And Key Evaluation
Indicators,
2023
Chinese Flight Test Establishment, Xi'an 710089, China; Key Laboratory of Flight Simulation Aeronautical Technology of AVIC, Xi'an 710089, China
Analysis Of Autonomous Aerial Refueling Capability Requirements And Key Evaluation Indicators, Quan Zou, Yixin Hua, Zhu Shao, Wenbi Zhao
Journal of System Simulation
Abstract: From the perspective of flight tests, how to evaluate the autonomous aerial refueling (AAR) capability and select key indicators for evaluation is a key problem to be solved for AAR trials. The standards requirements of aerial refueling and manned aircraft aerial refueling experience in China and abroad are analyzed. The total capability of AAR is studied, and key evaluation indicators in the AAR whole process including rendezvous, formation, docking, refueling, and disengagement are proposed. The evaluation method is demonstrated in both numerical simulation and hardware-in-loop test environments. Finally, the key indicators affecting the docking success of AAR are analyzed, …
Imitative Generation Of Optimal Guidance Law Based On Reinforcement Learning,
2023
Beijing Simulation Center, Beijing 100854, China
Imitative Generation Of Optimal Guidance Law Based On Reinforcement Learning, Zhengxuan Jia, Tingyu Lin, Yingying Xiao, Guoqiang Shi, Hao Wang, Bi Zeng, Yiming Ou, Pengpeng Zhao
Journal of System Simulation
Abstract: Under the background of high-speed maneuvering target interception, an optimal guidance law generation method for head-on interception independent of target acceleration estimation is proposed based on deep reinforcement learning. In addition, its effectiveness is verified through simulation experiments. As the simulation results suggest, the proposed method successfully achieves head-on interception of high-speed maneuvering targets in 3D space and largely reduces the requirement for target estimation with strong uncertainty, and it is more applicable than the optimal control method.
