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Articles 751 - 780 of 4159
Full-Text Articles in Systems Science
Modeling And Analysing Of Complex Combat Systems Based On Symbiosis Theory, Xiangrui Tian, Jie Ying, Rui Yao, Xiaodong Wan
Modeling And Analysing Of Complex Combat Systems Based On Symbiosis Theory, Xiangrui Tian, Jie Ying, Rui Yao, Xiaodong Wan
Journal of System Simulation
Abstract: As the combat systems develop towards clustering, coordination, unmanned, and intelligent direction, traditional combat system modeling methods are unable to reflect the complexity and intelligence of the combat systems. By drawing on symbiosis theory, this paper models and analyzes complex combat systems, and decomposes the complex combat system into various subsystems according to combat missions. The combat units, interaction modes, and combat environments in the subsystems are analyzed. The paper builds mathematical models to capture the collaborative interaction relationships between combat units, finally constructing a symbiotic model of complex combat systems. By the symbiosis principles and methods, quantitative analysis …
Action Recognition Model Of Directed Attention Based On Cosine Similarity, Chen Li, Ming He, Chen Dong, Wei Li
Action Recognition Model Of Directed Attention Based On Cosine Similarity, Chen Li, Ming He, Chen Dong, Wei Li
Journal of System Simulation
Abstract: Aiming at the lack of directionality of traditional dot product attention, this paper proposes a directed attention model (DAM) based on cosine similarity. To effectively represent the direction relationship between the spatial and temporal features of video frames, the paper defines the relationship function in the attention mechanism using the cosine similarity theory, which can remove the absolute value of the relationship between features. To reduce the computational burden of the attention mechanism, the operation is decomposed from two dimensions of time and space. The computational complexity is further optimized by combining linear attention operation. The experiment is divided …
Overall Scheme Design And Integration Testing Of Hardware-In-The-Loop Simulation Of Guidance And Control System, Xiaofei Chang, Jiayue Jiao, Kang Chen, Wenxing Fu, Jie Yan
Overall Scheme Design And Integration Testing Of Hardware-In-The-Loop Simulation Of Guidance And Control System, Xiaofei Chang, Jiayue Jiao, Kang Chen, Wenxing Fu, Jie Yan
Journal of System Simulation
Abstract: Hardware-in-the-loop simulation system is a complex distributed simulation system, and its design and integration directly affect the system performance and construction goals. Based on years of experience, this paper first summarizes the design of the overall scheme and analyzes the performance requirements of real-time, compatibility, scalability, and security. Then, the paper describes the overall scheme of a typical hardware-in-the-loop simulation system, including the functional hierarchy, operation mechanism, and structural composition. Finally, it summarizes the contents and steps of the system integration testing, acceptance testing, and credibility evaluation method.
Emergency Material Scheduling Based On Discrete Shuffled Frog Leaping Algorithm, Xiaoning Shen, Zhongpei Ge, Chengbin Yao, Liyan Song, Yufang Wang
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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 …
Experimental Data For: "Effects Of Network Connectivity And Functional Diversity Distribution On Human Collective Ideation", Yiding Cao, Yingjun Dong, Minjun Kim, Neil G. Maclaren, Sriniwas Pandey, Shelley D. Dionne, Francis J. Yammarino, Hiroki Sayama
Experimental Data For: "Effects Of Network Connectivity And Functional Diversity Distribution On Human Collective Ideation", Yiding Cao, Yingjun Dong, Minjun Kim, Neil G. Maclaren, Sriniwas Pandey, Shelley D. Dionne, Francis J. Yammarino, Hiroki Sayama
Systems Science and Industrial Engineering Faculty Scholarship
This is the dataset collected from our online human-subject experiments described in the following manuscript:
Yiding Cao, Yingjun Dong, Minjun Kim, Neil G. MacLaren, Sriniwas Pandey, Shelley D. Dionne, Francis J. Yammarino, and Hiroki Sayama:
"Effects of Network Connectivity and Functional Diversity Distribution on Human Collective Ideation"
https://arxiv.org/abs/2307.04284
A Human-Centered Framework For Oncological Healthcare System Modeling Applied To Mobile Radiation Delivery, Alex Price
A Human-Centered Framework For Oncological Healthcare System Modeling Applied To Mobile Radiation Delivery, Alex Price
Doctoral Dissertations
"Healthcare systems engineering is challenging due to the complexity, geographic expansiveness, inertial properties, and the heterogeneous sub-systems, with varying vested interests. Additionally, humans comprise many of the forms and functions, and are independent, with resistance and uncertainty in their decision-making that adds complexity. Human-centered systems modeling approaches are therefore needed to capture this unique aspect of a healthcare system and to enhance understanding of emergent healthcare properties. This dissertation focuses on integrating systems modeling within healthcare and emphasizes the importance of incorporating human decision-making. Moreover, the incorporation of a human-centered approach yields particularly valuable insights into the decision-making processes 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
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 …
Cybersecurity Awareness And Risks Among Students, Staff & Faculty At The University Of North Alabama, Jerry Lwamba
Cybersecurity Awareness And Risks Among Students, Staff & Faculty At The University Of North Alabama, Jerry Lwamba
Theses
As individuals and organizations become significantly connected to the internet, cybercriminals find an increasing number of ways to exploit their targets (Broadhurst, 2018). This study explores the world of cybersecurity awareness of risks associated with online activities within the University of North Alabama (UNA). This research aims to assess the level of cybersecurity awareness of risks university stakeholders face, and to also understand behaviors that expose them to cybercrime and emphasize the urge for comprehensive cybersecurity best practices. When cybercriminals employ tactics such as spam, phishing, or spear phishing in their attempts to break into network systems, distribute malware, or …
Mouralherwaqh Coastal Wetland Road Crossing Da'luk, Romel Robinson Ii
Mouralherwaqh Coastal Wetland Road Crossing Da'luk, Romel Robinson Ii
Cal Poly Humboldt theses and projects
The integration of Indigenous and Western science plays an essential role in Tribally led collaborations for land management. This process of woven sciences is rooted in reciprocal relations and partnerships guided by Tribal Nations. Our cohort was invited by Wiyot Tribal Representatives to investigate a culvert located within the wetlands of Mouralherwaqh— a parcel of land reacquired by the Wiyot Tribe in 2022. This document seeks to share our experience and analysis as part of the Wiyot Tribe’s broader journey in navigating ecocultural restoration projects within Mouralherwaqh. The four community interests we investigated for the wetland crossing included a resized …
Interpersonal Skills In A Sociotechnical System: A Training Gap In Flight Decks, Kimberly Perkins, Sourojit Ghosh, Crystal Hall
Interpersonal Skills In A Sociotechnical System: A Training Gap In Flight Decks, Kimberly Perkins, Sourojit Ghosh, Crystal Hall
Journal of Aviation/Aerospace Education & Research
This research analyzed the perceptions of interpersonal skills on established aviation safety models, Crew Resource Management (CRM), and Threat and Error Management (TEM) using feedback from industry pilots. The flight deck is a sociotechnical system where much research has focused on the technical aspect, whereas we spotlight its socio aspect. The aviation industry must invest in training pilots on interpersonal skills to enhance safety through increased efficacy of safety models integrated throughout existing training programs. A 34-question survey was disseminated across both commercial and business aviation pilots (N=822). We explored three research questions regarding pilots’ perceived training on interpersonal skills …
Integrated Organizational Machine Learning For Aviation Flight Data, Michael J. Pritchard, Austin T. Walden, Paul J. Thomas
Integrated Organizational Machine Learning For Aviation Flight Data, Michael J. Pritchard, Austin T. Walden, Paul J. Thomas
Journal of Aviation/Aerospace Education & Research
Increased availability of data and computing power has allowed organizations to apply machine learning techniques to various fleet monitoring activities. Additionally, our ability to acquire aircraft data has increased due to the miniaturization of small form factor computing machines. Aircraft data collection processes contain many data features in the form of multivariate time series (continuous, discrete, categorical, etc.) which can be used to train machine learning models. Yet, three major challenges still face many flight organizations: 1) integration and automation of data collection frameworks, 2) data cleanup and preparation, and 3) developing an embedded machine learning framework. Data cleanup and …
Leveraging Redundancy As A Link Between Spreading Dynamics On And Of Networks, Felipe Xavier Costa
Leveraging Redundancy As A Link Between Spreading Dynamics On And Of Networks, Felipe Xavier Costa
Electronic Theses & Dissertations (2024 - present)
A constant quest in network science has been in the development of methods to identify the most relevant components in a dynamical system solely via the interaction structure amongst its subsystems. This information allows the development of control and intervention strategies in biochemical signaling and epidemic spreading. We highlight the relevant components in heterogeneous dynamical system by their patterns of redundancy, which can connect how dynamics affect network topology and which pathways are necessary to spreading phenomena on networks. In order to measure the redundancies in a large class of empirical systems, we develop the backbone of directed networks methodology, …
Co-Evolving Multi-Agent Transfer Reinforcement Learning Via Scenario Independent Representation, Ayesha Siddiqua
Co-Evolving Multi-Agent Transfer Reinforcement Learning Via Scenario Independent Representation, Ayesha Siddiqua
Graduate Theses/Dissertations
Multi-Agent Reinforcement Learning (MARL) addresses complex tasks involving cooperation and competition among agents, training them to develop optimal policies for collective goals. However, facilitating simultaneous learning for multiple agents is challenging because the complexity increases rapidly with the number of agents. Current methods encompass a variety of centralized, decentralized, semi-centralized, and hybrid approaches to balance the trade-offs between computational efficiency, scalability, and coordination in MARL. In this study, I employed a centralized training with semi-centralized execution (CTSCE) framework, utilize both local observations from agents and abstracted global observations to effectively train agents in cooperative environments. Additionally, earning complex, domain-specific tasks …
Airport Operational Efficiency Evaluation Based On Combined Weighting-Topsis Model, Jie Hu, Fan Bao
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 …