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Articles 691 - 720 of 4243

Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering

Emergency Material Scheduling Based On Discrete Shuffled Frog Leaping Algorithm, Xiaoning Shen, Zhongpei Ge, Chengbin Yao, Liyan Song, Yufang Wang Jan 2024

Emergency Material Scheduling Based On Discrete Shuffled Frog Leaping Algorithm, Xiaoning Shen, Zhongpei Ge, Chengbin Yao, Liyan Song, Yufang Wang

Journal of System Simulation

Abstract: A mathematical model of emergency material scheduling after earthquakes is built. The model evaluates the emergency degree of each disaster area based on the disaster situation and designs a method to split the demand of the disaster area, improving the efficiency of vehicle utilization. To solve the model, this paper proposes a discrete shuffled frog leaping algorithm with multi-resource learning. The multiple information sources introduced by the proposed algorithm can expand the search direction and reduce the assimilation speed of the population in the algorithm. Second, the worst individual in each subgroup can learn the effective information in the …


Combat Effectiveness Evaluation Method Of Homogeneous Cluster Equipment System Based On Rlomag+Eas, Guohui Zhang, Ang Gao, Ya'nan Zhang Jan 2024

Combat Effectiveness Evaluation Method Of Homogeneous Cluster Equipment System Based On Rlomag+Eas, Guohui Zhang, Ang Gao, Ya'nan Zhang

Journal of System Simulation

Abstract: The equipment system is the reflection of the combat system from the perspective of equipment. The research on the combat effectiveness evaluation of the equipment system is of great practical significance for the optimization, construction, and development of the equipment system. Cluster equipment combat system confrontation is characterized by large-scale, highly dynamic and strong confrontation, and it is difficult to directly evaluate combat effectiveness with traditional methods. Aiming at the single task homogeneous cluster equipment system (such as UAV reconnaissance swarm and ground unmanned platform fire assault cluster), this paper regards the confrontation process of equipment system as the …


Optimization On Cold Chain Distribution Routes Considering Carbon Emissions Based On Improved Ant Colony Algorithm, Huifang Bao, Jie Fang, Jinsi Zhang, Chuansheng Wang Jan 2024

Optimization On Cold Chain Distribution Routes Considering Carbon Emissions Based On Improved Ant Colony Algorithm, Huifang Bao, Jie Fang, Jinsi Zhang, Chuansheng Wang

Journal of System Simulation

Abstract: As the comprehensive distribution cost is not considered comprehensively in the current cold chain distribution route optimization, this paper builds a path optimization model to minimize the comprehensive distribution cost. The model combines with the characteristics of fresh distribution, and comprehensively considers the transportation cost, carbon emission, refrigeration, cargo damage and time window constraints during cold chain transportation. Then, an improved ant colony algorithm is designed to solve this model. At the initial stage, the genetic algorithm is adopted to generate the initial pheromone, and then the ant colony algorithm is applied to conduct the subsequent optimization search. The …


Recursive Subspace-Based Model Refinement Method For Digital Twin Of Thermal Power Unit, Yanbo Zhao, Yuanli Cai, Huaizhong Hu Jan 2024

Recursive Subspace-Based Model Refinement Method For Digital Twin Of Thermal Power Unit, Yanbo Zhao, Yuanli Cai, Huaizhong Hu

Journal of System Simulation

Abstract: Due to factors such as simplified assumptions or equipment characteristic deviation, modeling errors are inevitable in the mechanism modeling of thermal power units. To deal with the problem, this paper proposes a novel model refinement method based on recursive subspace for the digital twin of thermal power units. Firstly, the digital twin models are built based on mechanism analysis and combined with small sample data of typical conditions, ensuring interpretability and generalization performance. Secondly, based on the recursive subspace identification method, the refinement model is built and updated online in real time to compensate for the modeling error, improving …


Driving Method Of Virtual Multi-Person Disassembly And Assembly Task For Aeroengine, Qiuwei Zeng, Zhaoyong Hu, Zhile Wang, Ruilin Zhang, Gang Zou Jan 2024

Driving Method Of Virtual Multi-Person Disassembly And Assembly Task For Aeroengine, Qiuwei Zeng, Zhaoyong Hu, Zhile Wang, Ruilin Zhang, Gang Zou

Journal of System Simulation

Abstract: To meet the needs of virtual multi-person collaborative disassembly and assembly system for different disassembly and assembly tasks, this paper proposes a data-driven method with configurable task sequence. Taking an aeroengine prototype as the research object, the paper studies the task elements of multi-person collaborative disassembly and assembly. It parameterizes and expresses the task based on JSON (JavaScript object notation) and drives the task sequence by JSON parametrical files, defining the interactive operation of each task step. The practice shows that this method is applied to the multi-person collaborative disassembly and assembly system, which makes the system configurable and …


Result Validation Method Of Simulation Models Based On Piecewise Feature Extraction, Yucheng Luo, Ming'en Zhang, Fei Liu, Yingbo Lu, Feng Ye Jan 2024

Result Validation Method Of Simulation Models Based On Piecewise Feature Extraction, Yucheng Luo, Ming'en Zhang, Fei Liu, Yingbo Lu, Feng Ye

Journal of System Simulation

Abstract: Verification, validation, and accreditation (VV&A) is a key means to ensure the credibility of simulation models, and model validation is the core link. In view of the unavailability of reference data, various sources of reference data, and strong subjectivity of expert validation in the result validation of the missile flight simulation model, a result validation method for the missile flight simulation model based on piecewise feature extraction of time series was proposed. Specifically, a comprehensive piecewise linear method for time series was first proposed. The method consisted of a linear piecewise algorithm based on the second-order derivative for extracting …


Obstacle Avoidance Motion In Mobile Robotics, Yunchao Tang, Shaojun Qi, Lixue Zhu, Xianrong Zhuo, Yunqi Zhang, Fan Meng Jan 2024

Obstacle Avoidance Motion In Mobile Robotics, Yunchao Tang, Shaojun Qi, Lixue Zhu, Xianrong Zhuo, Yunqi Zhang, Fan Meng

Journal of System Simulation

Abstract: The advancement of artificial intelligence technology has significantly enhanced the utilization of mobile robots in various fields such as industry, aerospace, and agriculture. The autonomous obstacle avoidance capability of these robots is crucial to the safety and efficiency of their operations in diverse settings. Path planning, a key technology in obstacle avoidance, plays an essential role in the overall performance of these systems. This paper presents a comprehensive review of path planning technology for mobile robots, categorizing the algorithms into global planning and local obstacle avoidance according to their operational requirements. Specific focus is given to the global planning …


Intelligent Airport Crowd Management Technology Based On Digital Twin, Jinghui Zhong, Yutian Lin, Wenqiang Li, Wentong Cai Jan 2024

Intelligent Airport Crowd Management Technology Based On Digital Twin, Jinghui Zhong, Yutian Lin, Wenqiang Li, Wentong Cai

Journal of System Simulation

Abstract: Given the need for intelligent emergency control and management of airport crowds, a smart control scheme for airport crowds based on digital twin is proposed. The scheme constructs an integrated crowd control system framework with four dimensions, including digital layer, modeling layer, functional layer, and application layer. It discusses and demonstrates the application effect of five important application modules. By using a data-driven crowd simulation model and intelligent optimization algorithm, the proposed scheme realizes the dynamic prediction and control optimization of the airport crowd status. The scheme can effectively improve the efficiency and intelligence level of airport crowd control …


Multi-Uav Collaborative Trajectory Planning Algorithm For Urban Ultra-Low-Altitude Air Transportation Scenario, Jie Cheng, Yuan Zheng, Chenglong Li, Bo Jiang Jan 2024

Multi-Uav Collaborative Trajectory Planning Algorithm For Urban Ultra-Low-Altitude Air Transportation Scenario, Jie Cheng, Yuan Zheng, Chenglong Li, Bo Jiang

Journal of System Simulation

Abstract: The rapid development of the drone industry has promoted the opening of low-altitude, forming a wave of ultra-low-altitude air transportation in cities sweeping over the world. However, the existing trajectory planning algorithms do not consider the division method and operating rules of the ultra-low-altitude airspace. They are not suitable for the collaborative trajectory planning of multiple UAVs in the urban ultra-low-altitude air transportation scenario, which may restrict the development of the ultra-low-altitude air transportation industry. This paper explores a multi-UAV collaborative trajectory planning method for urban ultra-low-altitude air transportation scenario based on the airspace flight altitude layer architecture. Specifically, …


Multi-View Depth Estimation Based On Adaptive Space Feature Enhancement, Dong Wei, Huan Liu, Xiaohan Zhang, Changkai Li, Tianyi Sun, Ziyou Zhang Jan 2024

Multi-View Depth Estimation Based On Adaptive Space Feature Enhancement, Dong Wei, Huan Liu, Xiaohan Zhang, Changkai Li, Tianyi Sun, Ziyou Zhang

Journal of System Simulation

Abstract: A multi-view depth estimation algorithm based on adaptive space feature enhancement (ASFE) is presented to improve the multi-view depth estimation accuracy. A multi-scale feature extraction module composed of an improved feature pyramid network (FPN) and ASFE is designed. This module obtains multi-scale feature maps with global context-aware information and coordinate information. The residual learning network is used to optimize the depth map to prevent the problem of blurred reconstructed edges in multiple convolution operations. The proposed algorithm constructs a focal loss function through the idea of classification to enhance the prediction ability of the network model. The experimental results …


Visual Monitoring System Of Digital Twin Workshop For Process Manufacturing, Yanchao Yin, Jiasheng Feng, Bin Yi, Wang Li, Qingwen Yin Jan 2024

Visual Monitoring System Of Digital Twin Workshop For Process Manufacturing, Yanchao Yin, Jiasheng Feng, Bin Yi, Wang Li, Qingwen Yin

Journal of System Simulation

Abstract: To solve the problem of poor real-time and accuracy of process manufacturing monitoring, this paper proposes a visual monitoring system architecture of digital twin workshop based on production factor data, production process, and multi-process equipment entity object amid the rapid development of digital twin technology and increasingly close integration with the manufacturing industry. Twin modeling is conducted on multi-process coupling production line entity objects from multiple dimensions such as element, state, and operation logic. Based on key technologies of data collection and transmission of OPC UA (OLE for process control unified archiecture) unified architecture and real-time drive of the …


Reentrant Hybrid Flow Shop Scheduling Problem Based On Moma, Hongbin Qin, Chenxiao Li, Hongtao Tang, Feng Zhang Jan 2024

Reentrant Hybrid Flow Shop Scheduling Problem Based On Moma, Hongbin Qin, Chenxiao Li, Hongtao Tang, Feng Zhang

Journal of System Simulation

Abstract: For the characteristics of multi-variety, large-scale and mixed-flow production of reentrant manufacturing systems, the reentrant hybrid flow shop scheduling problem with batch processors (BPRHFSP) is constructed, and an improved multi-objective mayfly algorithm (MOMA) is proposed for BPRHFSP. Firstly, decoding rules for single-piece processing stage and batch-processing stage are proposed. Then, a reverse learning initialization strategy based on logistic chaotic mapping is designed to improve the quality of the initial solution of the algorithm, also an improved mayfly mating strategy is designed to improve the local search ability of MOMA. Finally, a VND-based mayfly movement strategy is designed based on …


Research On Campus Epidemic Evolution Based On Multi-Scale Modeling And Simulation In Microscopic & Microscopic View, Mingwei Hu, Wenjie Yang Jan 2024

Research On Campus Epidemic Evolution Based On Multi-Scale Modeling And Simulation In Microscopic & Microscopic View, Mingwei Hu, Wenjie Yang

Journal of System Simulation

Abstract: High density of population leads to high possibility of cross-infection. It is necessary to focus on campus epidemic prevention and control. Basing on existing studies in macroscopic or microscopic view, this paper proposed a multi-scale means to analyze a short-term evolution of Corona virus disease 2019 (COVID-19) on campus and estimated the efficiency of prevention strategies. Macroscopic model was based on the susceptible-exposed-infections-recovered(SEIR) model, which exported the time curve of the number of asymptomatic patients and symptomatic patients. Microscopic model combined discrete event simulation modeling and agent-based modeling to simulate the behavior of campus students and the state evolution …


Heterogeneous Multi-Ant Colony Algorithm Combining Competitive Interaction Strategy And Eliminatingreconstructing Mechanism, Chen Feng, Xiaoming You, Sheng Liu Jan 2024

Heterogeneous Multi-Ant Colony Algorithm Combining Competitive Interaction Strategy And Eliminatingreconstructing Mechanism, Chen Feng, Xiaoming You, Sheng Liu

Journal of System Simulation

Abstract: The traditional ant colony algorithm has many problems in convergence and diversity when solving the traveling salesman problem (TSP). Therefore, this paper proposes a heterogeneous multi-ant colony algorithm that combines the competitive interaction strategy and the eliminating-reconstructing mechanism (CEACO) to overcome these shortcomings. Firstly, the algorithm uses a competitive interaction strategy, which adjusts the interaction period adaptively according to the Hamming distance of different groups in different periods. Competition coefficients are adopted to differentiate matching interaction objects for interaction. The matched objects interact with each other through the optimal solution and pheromone matrix. This mechanism achieves a balance between …


Multi-Model Soft Sensor Modeling Under Help-Training Strategy, Luosuyang He, Weili Xiong Jan 2024

Multi-Model Soft Sensor Modeling Under Help-Training Strategy, Luosuyang He, Weili Xiong

Journal of System Simulation

Abstract: Due to the strong nonlinearity, multi-stage coupling, and the small number of labeled samples in complex industrial processes, it is difficult for traditional global soft sensor models to accurately describe the whole process. Therefore, a multi-model soft sensor modeling method under the helptraining strategy is proposed. This method uses a fuzzy C-means (FMC) clustering algorithm to mine similar samples in the sample set and build several sub-models. By introducing the help-training strategy, a collaborative training framework based on main and auxiliary learners is formed, and a confidence evaluation mechanism is designed to eliminate error samples and expand the modeling …


Strategy Optimization Method Of Multi-Dimension Projection Based On Deep Reinforcement Learning, Jing An, Guangya Si, Lei Zhang Jan 2024

Strategy Optimization Method Of Multi-Dimension Projection Based On Deep Reinforcement Learning, Jing An, Guangya Si, Lei Zhang

Journal of System Simulation

Abstract: Based on the perfect performance of deep reinforcement learning (DRL) in strategy optimization, this paper proposes a strategy optimization method of action taking the multi-dimension projection action as the main research object. The method combines the simulation experiment method with the DRL method. After analyzing the current situation of strategy optimization research, the deep learning framework is selected according to the research problems, and a DRL multi-dimension projection strategy model based on the asynchronous advantage actor-critic (A3C) algorithm is constructed. Through simulation experiments, the interactive learning between the DRL model and the simulation of "out of the loop" is …


A Simulation Method Based On Multi-Source Sensors For Aircraft Type Identification, Shaozhu Gu, Yuxin Ying, Huajie Zhang, Yiqi Tong Jan 2024

A Simulation Method Based On Multi-Source Sensors For Aircraft Type Identification, Shaozhu Gu, Yuxin Ying, Huajie Zhang, Yiqi Tong

Journal of System Simulation

Abstract: Existing simulation methods for aircraft type identification mainly focus on a single sensor and a single target. They do not consider the joint acquisition of aircraft parameters by various sensor devices such as optoelectronics, radar, and electronic detection in real scenarios, leading to the simple simulation scenarios. This paper proposes a simulation platform based on multi-source sensors. Specifically, the platform includes an infrared image simulator that uses a cycleGAN network to generate infrared images of the aircraft, a flight simulator that adopts the three-degree-of-freedom flight control method to generate the movement trajectory of the aircraft, a radar simulator, that …


The Hazard Prediction Problem, Mary E. Helander, Brendan Smith, Sylvia Charchut, Erika Swiatowy, Calvin Nau, Gregory Cavaretta, Timothy Schuler, Adam Schunk, Héctor Ortiz-Peña Jan 2024

The Hazard Prediction Problem, Mary E. Helander, Brendan Smith, Sylvia Charchut, Erika Swiatowy, Calvin Nau, Gregory Cavaretta, Timothy Schuler, Adam Schunk, Héctor Ortiz-Peña

Social Science - All Scholarship

This work formulates the hazard prediction problem while addressing the research question: Can machine learning create a model to automatically recognize patterns that correspond to hazard state conditions during a mission-critical operation? Supervised learning models were trained and tested on data observed from mission simulators, which allowed for safe observation of dynamic system states and undesirable casualty events. The prediction task was formulated as a binary classification problem, producing the probability of being in a hazard state at time t and providing situational awareness of a possible imminent loss. Several modeling architectures were investigated: neural networks, logistic regression, a support …


Integrating Generative Artificial Intelligence With Systems Architecting Diagram Creation: Advancement, Challenges, Opportunities And Future Perspectives, Cansu Yalim, Holly H. Handley Jan 2024

Integrating Generative Artificial Intelligence With Systems Architecting Diagram Creation: Advancement, Challenges, Opportunities And Future Perspectives, Cansu Yalim, Holly H. Handley

Engineering Management & Systems Engineering Faculty Publications

Generative AI (GenAI) serves as a powerful tool that can create a wide range of content, including but not limited to text, speech, images, code, videos, and 3D models. ChatGPT stands out as a particularly appealing Generative Pretrained Transformer (GPT) model that offers supplementary capabilities through GPTs and plugins. These extensions enable users to engage with the chatbot and improve its functionality, surpassing mere content generation. Our study delves into the potential of ChatGPT, specifically GPT-4, to expedite the creation of diagrams to support the system architecting process. To this end, we explored the use of ChatGPT's Diagrams Show Me …


‘I Know It When I See It’– Developing Quality Schedules Considering Subjective Or Unspecified Criteria, Douglas L. Moody Jan 2024

‘I Know It When I See It’– Developing Quality Schedules Considering Subjective Or Unspecified Criteria, Douglas L. Moody

Publications and Research

Most timetabling problems have a given objective function to measure the quality of a solution. However, users may have a “I know it when I see it” recognition of a quality schedule, without specifying the complete basis for their judgment. In this situation, the objective function cannot be exclusively used as a solution quality measurement. This work presents an AI based approach to aid in categorizing the solution’s quality when the users have not explicitly defined all factors used in their criteria.


Conflict Profiles And Team Outcomes In Cross-Disciplinary Teams: An Integrated Latent Profile Analysis And Natural Language Processing Approach, Francisco Cima, Pilar Pazos Jan 2024

Conflict Profiles And Team Outcomes In Cross-Disciplinary Teams: An Integrated Latent Profile Analysis And Natural Language Processing Approach, Francisco Cima, Pilar Pazos

Engineering Management & Systems Engineering Faculty Publications

Team conflict is a naturally emerging phenomenon resulting from individuals' interactions during project execution. Cross-disciplinary teams can experience higher levels of conflict than single-discipline teams because of the increased diversity of knowledge and perspectives. Research has shown that team conflict can emerge from different types of disagreements (cognitive and interpersonal), which have different implications for team functioning. Past empirical research has focused on the impact of both conflict types independent from each other while overlooking their combined effects. This work examines the conflict profiles resulting from the combined levels of interpersonal and cognitive disagreements and their association with team outcomes. …


Advancing Household Robotics: Deep Interactive Reinforcement Learning For Efficient Training And Enhanced Performance, Arpita Soni, Sujatha Alla, Suresh Dodda, Hemanth Volikatla Jan 2024

Advancing Household Robotics: Deep Interactive Reinforcement Learning For Efficient Training And Enhanced Performance, Arpita Soni, Sujatha Alla, Suresh Dodda, Hemanth Volikatla

Engineering Management & Systems Engineering Faculty Publications

The market for domestic robots—made to perform household chore, is growing as these robots relieve people of everyday responsibilities. Domestic robots are generally welcomed for their role in easing human labour, in contrast to industrial robots, which are frequently criticised for displacing human workers. But before these robots can carry out domestic chores, they need to become proficient in a number of minor activities, such as recognizing their surroundings, making decisions, and picking up on human behaviours. Reinforcement learning, or RL, has emerged as a key robotics technology that enables robots to interact with their environment and learn how to …


Airport Operational Efficiency Evaluation Based On Combined Weighting-Topsis Model, Jie Hu, Fan Bao Dec 2023

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 …


Automatic Target Recognition Of Substation 3d Scene For Digital Twin, Qian Tu, Jun Li, Dongliang Fan, Qi Kong, Jie Shen Dec 2023

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 …


Research On 3d Object Detection Method With Cross-Module Attention, Renjie Xu, Xiaoming Zhang, Chen Wang, Peng Wu Dec 2023

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 …


Task Scheduling For Internet Of Vehicles Based On Deep Reinforcement Learning In Edge Computing, Xiang Ju, Shengchao Su, Chaojie Xu, Beibei He Dec 2023

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 …


Research On Digital Twin Data Modeling And Evaluation Method Of Automated Container Terminal, Guoxuan Xu, Daofang Chang, Jiaqi Li, Qiang Ling Dec 2023

Research On Digital Twin Data Modeling And Evaluation Method Of Automated Container Terminal, Guoxuan Xu, Daofang Chang, Jiaqi Li, Qiang Ling

Journal of System Simulation

Abstract: To make full use of the massive operation data of automated container terminals and further realize the digital and intelligent transformation of terminals driven by digital twin, a method for digital twin data modeling and effect verification and evaluation of automated container terminals is proposed. The application framework and operation mechanism based on digital twin are studied. Based on the data processing logic of digital twin framework, a method of terminal operation process evolution and dynamic data modeling based on digital twin is proposed. To verify whether the data could meet the effective operation of the digital twin, a …


Modeling And Simulation On Production Logistics Of Intelligent Workshop Manufacturing System Based On Efsm, Liuzhen Li, Chao Jin, Tingyu Lin, Yaoqin Zhu Dec 2023

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 …


Development Of Several Typical Virtual Reality Fusion Technologies, Qiqi Feng, Zhiming Dong, Wencheng Peng, Yi Dai, Bingshan Si Dec 2023

Development Of Several Typical Virtual Reality Fusion Technologies, Qiqi Feng, Zhiming Dong, Wencheng Peng, Yi Dai, Bingshan Si

Journal of System Simulation

Abstract: Virtual reality fusion can realize the two-way interaction, mapping and linkage between virtual world and physical world, which attracts the attention of countries in the world. In order to sort out and make statistics on concept connotation, academic status and application of the related new technologies, digital twin, cyber-physical systems, metaverse and live-virtual-constructive simulation are taken as representatives. The comparison on the development process, functional characteristics, target trends, etc. is carried out.


Data Simulation Testing Framework For Complex Process Equipment Software, Jinkun Zhang, Longfei Shi, Chi Hu, Hao Zhang, Yonghui Yang Dec 2023

Data Simulation Testing Framework For Complex Process Equipment Software, Jinkun Zhang, Longfei Shi, Chi Hu, Hao Zhang, Yonghui Yang

Journal of System Simulation

Abstract: Due to the complex task, tight coupling, strict timing, and a large amount of interchange data, the technical threshold of automated testing of bus communication equipment software is high, and the implementation is difficult. The ideas of data-driven testing and keyword-driven testing are introduced, and a data simulation testing framework is proposed. Configuration rules are formulated and implemented in the framework. Testers can simulate peripheral data for complex process equipment software and implement automated testing by only focusing on the task analysis, and configuring interchange data and keywords. There is no need to develop test scripts, which reduces the …