Predictive Control Method Of Peak Hour Passenger Flow At Urban Rail Station,
2022
Department of Civil Engineering, Tsinghua University, Beijing 100084, China;
Predictive Control Method Of Peak Hour Passenger Flow At Urban Rail Station, Xiaohe Li, Jianping Wu, Depin Peng
Journal of System Simulation
Abstract: With the rapid development of subway in China, the urban rail station, especially the transfer station, is prone to generate passenger congestion in the peak period. After analyzing the types of passenger flow in and out of the platform, a predictive control model of passenger flow is established based on the discrete linear quadratic optimal control theory. Taking Fuxingmen Station as an example, the simulation environment of the station is built by using the simulation software of Anylogic. The historical passenger flow data in peak period and the optimal passenger flow control sequence obtained by solving the passenger flow …
Study And Effect Evaluation On The Setting Of Contraflow Left-Turn At Intersections,
2022
School of Traffic Management, People's Public Security University of China, Beijing 102163, China;
Study And Effect Evaluation On The Setting Of Contraflow Left-Turn At Intersections, Zhao Dan, Xuejun Niu, Shuhao Zhang, Jiaxu Wei
Journal of System Simulation
Abstract: Contraflow left-turn is one of the traffic organization ways at intersections. By analyzing the setting parameters of the contraflow left-turn, the length and the range of the contraflow left-turn lane, the constrained conditions of the contraflow left-turn are determined, and the applicable conditions are determined from the road, traffic and signal control. VISSIM software is used to analyze a road intersection, simulate and evaluate the indicators related to the intersection entrance, optimize the timing plan of contraflow left-turn lane, and validate the feasibility and advantages of contraflow left-turn lane. The results show that the intersection delays are reduced by …
Variety Recognition Based On Deep Learning And Double-Sided Characteristics Of Maize Kernel,
2022
1. Institute of Agricultural Economics and Information, Henan Academy of Agricultural Sciences, Zhengzhou 450002, China; ;2. Henan Engineering and Technology Research Center for Intelligent Agriculture, Zhengzhou 450002, China; ;
Variety Recognition Based On Deep Learning And Double-Sided Characteristics Of Maize Kernel, Feng Xiao, Zhang Hui, Zhou Rui, Qiao Lu, Wei Dong, Dandan Li, Yuyao Zhang, Guoqing Zheng
Journal of System Simulation
Abstract: In order to construct a maize kernel variety recognition model with high recognition accuracy and suitable for mobile phone application, a mobile phone is used to obtain maize kernel double-sided (embryonic and non-embryonic) images. Based on the lightweight convolutional neural network MobileNetV2 and transfer learning, a maize kernel image variety recognition model is constructed. In view of the existing research methods are mainly for single-sided recognition of maize kernel variety, the performance of single-sided and double-sided characteristics modeling and recognition is compared. The results show that the double-sided recognition accuracy of maize kernel double-sided characteristics modeling is 99.83%, which …
Track Deception Modeling Method Based On Multi-Jammer Cooperation,
2022
1. Rocket Force University of Engineering, Xi'an, 710025, China; ;
Track Deception Modeling Method Based On Multi-Jammer Cooperation, Wang Rui, Xiangyang Li, Zhili Zhang, Hongguang Ma
Journal of System Simulation
Abstract: The false track generated by the jammer formation is an effective interference measure against networked radars. This paper starts from the basic principle of false track generation and presents the model of the measurement error of the radar for the false track and the control error of the jammer formation. It also presents an analysis of the effects of these errors on the false track. The effectiveness of the false track is further analyzed through the confrontation scenario between the rectangular front formation of a certain type of equipment and networked radars. The simulation results show that the false …
Low Power Visual Odometry Technology Based On Monocular Depth Estimation,
2022
1. Science and Technology on Special System Simulation Laboratory, Beijing 100854, China; ;
Low Power Visual Odometry Technology Based On Monocular Depth Estimation, Ma Rong, Qiurui Chen, Zhang Han, Mei Zheng, Wang Rui, Wei Wei
Journal of System Simulation
Abstract: With the development of artificial intelligence, precision machinery and computing technology, micro-unmanned system will play an important role in the future battlefield. To solve the lack of monocular visual odometry scale, micro robot power consumption and load limits, the monocular depth estimation technology is introduced and a low view dataset is collected. A convolutional neural network to predict depth information from a single image is built, and the structure of neural network model is optimized. The depth estimation with monocular visual odometry are combined and deployed on JetsonNano. Experiments show that the combined monocular visual odometry can recover scale …
Research On Supply Chain Recovery Strategy Under Disruption Risks,
2022
1. Shanghai University, Shanghai 200444, China; ;
Research On Supply Chain Recovery Strategy Under Disruption Risks, Yang Yi, Peng Chen, Yujiu Yang, Yulong Wang
Journal of System Simulation
Abstract: Aiming at supply chain disruptions, two effective supply chain recovery strategies are proposed, namely, a supplier’s preset emergency inventory strategy and a manufacturer’s product change strategy, meanwhile, emergency inventory storage cost and products return rate after change are also taken into consideration. In order to maximize the manufacturer’s profit and customer satisfaction, a single-objective model and a bi-objective model are established, respectively. The optimization problems in the two models are transformed into mixed integer programming problems, moreover, corresponding solution algorithms are presented based on ILOG CPLEX. The simulation results show that the disruption recovery strategies proposed can not only …
Radar Emitter Signal Identification Via Distance Features,
2022
1. College of Electrical Engineering, Southwest Jiao tong University, Chengdu 610031, China; ;
Radar Emitter Signal Identification Via Distance Features, Yingkun Huang, Weidong Jin, Yan Kang, Jiehao Zhu
Journal of System Simulation
Abstract: Aiming at the problem that traditional recognition methods of radar emitter signal have low accuracy in low signal to noise ratio (SNR) environment, and are usually suitable for only several specific radar signals, an identification approach of radar signal based on distance features is proposed. Several cluster centers are extracted via the k-means algorithm, and the Dynamic Time Warping (DTW) values between the radar signal and the cluster center are calculated respectively, which are combined as the input features of k-Nearest Neighbor (k-NN) algorithm. The simulation results show that when the SNR is 3 dB, the identification rate …
Study On Prediction Of Crystal Properties Based On Deep Learning,
2022
1. College of Information Engineering, Yangzhou University, Yangzhou 225127, China; ;
Study On Prediction Of Crystal Properties Based On Deep Learning, Buwei Wang, Wang Min, Fan Qian, Ya'nan Wang, Hanwen Zhang, Yunliang Yue
Journal of System Simulation
Abstract: Predicting crystal properties using traditional machine learning methods requires complex feature engineering. In order to bypass time-consuming feature engineering, element network (ElemNet), representation learning from stoichiometry (Roost), compositionally-restricted attention-based network (CrabNet) and crystal graph convolution neural network (CGCNN) based on deep learning technology are used to simulate the formation energy, total energy per atom, band gap, and Fermi energy of crystal. The residual learning is introduced into CGCNN, and a crystal graph convolution residual neural network (CGCRN) is proposed. In the CGCRN, the number of hidden layers and the number of nodes in the hidden layers are increased, …
Improved Ant Colony Optimization Algorithm For Jamming Resource Allocation,
2022
1. Beijing Information Technology Co, Ltd, Beijing 100094, China; ;
Improved Ant Colony Optimization Algorithm For Jamming Resource Allocation, Qingyun Wang, Dezhong Jiao, Shi Shuo, Genyan Peng, Junhua Sun, Yuxin Duan
Journal of System Simulation
Abstract: Ant Colony Optimization (ACO) is a new intelligence optimization algorithm. When applied to jamming resource allocation, the velocity of convergence in optimization process is slow and the probability of obtaining the global optimal solution is low. In order to raise the efficiency of jamming resource allocation and the probability of getting global optimal solution, the attenuation factor is improved to a variable that changes according to the exponential function in optimization process. The attenuation factor is taken as a relatively small value in the initial search phase, and increases monotonically and exponentially as the number of iterations increases. Simulation …
Brief Review On Applying Reinforcement Learning To Job Shop Scheduling Problems,
2022
1. Beihang University, Beijing 100191, China; ;2. Engineering Research Center of Complex Product Advanced Manufacturing Systems, Ministry of Education, Beijing 100191, China;
Brief Review On Applying Reinforcement Learning To Job Shop Scheduling Problems, Xiaohan Wang, Zhang Lin, Ren Lei, Kunyu Xie, Kunyu Wang, Ye Fei, Chen Zhen
Journal of System Simulation
Abstract: Reinforcement Learning (RL) achieves lower time response and better model generalization in Job Shop Scheduling Problem (JSSP). To explain the current overall research status of JSSP based on RL, summarize the current scheduling framework based on RL, and lay the foundation for follow-up research, the backgrounds of JSSP and RL are introduced. Two simulation techniques commonly used in JSSP are analyzed and two commonly used frameworks for RL to solve JSSP are given. In addition, some existing challenges are pointed out, and related research progress is introduced from three aspects: direct scheduling, feature representation-based scheduling, and parameter search-based scheduling.
Hyperspectral Rx Anomaly Detection Method Based On The Fusion Of Spatial And Spectral Feature,
2022
Rocket Force University of Engineering, Xi'an 710025, China;
Hyperspectral Rx Anomaly Detection Method Based On The Fusion Of Spatial And Spectral Feature, Liu Xuan, Xiangyang Li, He Fang, Jianwei Zhao, Fenggan Zhang
Journal of System Simulation
Abstract: To address the problem that the hyperspectral anomaly detection algorithm does not make full use of the spatial information of the hyperspectral image and the detection accuracy is limited, a FSSRX (Fusing Spatial and Spectral Reed-Xiaol) anomaly detection algorithm that fuses spatial and spectrum information is proposed to improve the accuracy of hyperspectral anomaly detection. In FSSRX algorithm, the spatial feature of hyperspectral images is firstly extracted by the EMAP(Extended Multi-attribute Profile) method and the abnormal score of each pixel in spatial features is then calculated with RX detector. Meanwhile, RX anomaly detection is carried out directly on the …
Research On Model Reuse Technology Based On Semantic Matching And Composition,
2022
1. School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China; ;
Research On Model Reuse Technology Based On Semantic Matching And Composition, Xingyu Tian, Guangxun Zeng, Yunbo Gao, Lili Ye, Guanghong Gong, Li Ni
Journal of System Simulation
Abstract: In order to solve the data barriers between the conceptual model and the simulation scenario of the combat system, the intelligent mapping and model reuse technology of the simulation scenario is researched. The conceptual model is analyzed using DOM technology. Based on the ontology theory, the knowledge base of the combat domain is constructed and the web crawler is customized to build the domain thesaurus. Through the SWRL rule library, the reasoning engine is called to realize the relational reasoning at the semantic level. An intelligent matching algorithm is designed to map the semantic relationship to the combination relationship …
The Toyota Production System (Tps) In A Non-Traditional Manufacturing Environment: The Role Of Standardization In The Fast-Food Industry,
2022
University of Kentucky
The Toyota Production System (Tps) In A Non-Traditional Manufacturing Environment: The Role Of Standardization In The Fast-Food Industry, Kevin Mccracken
Theses and Dissertations--Manufacturing Systems Engineering
The Toyota Production System (TPS), also known as Lean Manufacturing (LM), was founded in the automotive industry and has contributed to Toyota’s decades of success. This has brought much attention to TPS and how this system may be implemented in other industries. Focusing on the TPS foundational element of standardization, this study examines the impact of target cycle time (TCT) on process fluctuation in a fast-food environment. In order to observe the effects of TCT, team members within 3 production lines were timed. Times were measured before and after the addition of a TCT to the Standardized Work (STW) in …
Importance Measure-Based Maintenance Strategy Considering Maintenance Costs,
2022
Old Dominion University
Importance Measure-Based Maintenance Strategy Considering Maintenance Costs, Chao Zhang, Yadong Zhang, Hongyan Dui, Shaoping Wang, Mileta M. Tomovic
Engineering Technology Faculty Publications
Maintenance is an important way to ensure the best performance of repairable systems. This paper considers how to reduce system maintenance cost while ensuring consistent system performance. Due to budget constraints, preventive maintenance (PM) can be done on only some of the system components. Also, different selections of components to be maintained can have markedly different effects on system performance. On the basis of the above issues, this paper proposes an importance-based maintenance priority (IBMP) model to guide the selection of PM components. Then the model is extended to find the degree of correlation between two components to be maintained …
Performing A Penetration Test On A Storage Network,
2022
The University of Akron
Performing A Penetration Test On A Storage Network, Scott Moskal
Williams Honors College, Honors Research Projects
A small storage network will be designed with two wired routers, one wireless router, a switch, two laptops, a desktop, and a Raspberry Pi. Both laptops will be connected to the wireless router. The HP laptop will run Parrot OS and the Acer laptop will run Windows 11. The wireless router will be connected to the second router via port eth0. The eth2 port on the second router will be connected to eth1 port of the third router. The third router will be connected to the eth0 port of the Netgear switch. The switch will have two VLANs. VLAN 10 …
Market Surveillance To Support Quality Assurance And Consumer Protection For The Solar Payg Products Market In East And West Africa,
2022
Cal Poly Humboldt
Market Surveillance To Support Quality Assurance And Consumer Protection For The Solar Payg Products Market In East And West Africa, Hamidah Naishur Nakimuli
Cal Poly Humboldt theses and projects
Off-grid Pay As You Go (PAYG) solar products have become one of the fastest-growing approaches to providing basic electricity services to off-grid households not only in Sub-Saharan Africa but also in many other parts of the world with limited or no access to the grid connection. However, sustainably growing the PAYG solar industry requires paying close attention to product quality from the point of manufacturing to the end user. This research examines how to best design market surveillance programs that ensure quality in off-grid PAYG solar products and strengthen the implementation and enforcement of quality standards in the off-grid solar …
Humans And The Core Partition: An Agent-Based Modeling Experiment,
2022
Old Dominion University
Humans And The Core Partition: An Agent-Based Modeling Experiment, Andrew J. Collins, Sheida Etemadidavan
Engineering Management & Systems Engineering Faculty Publications
Although strategic coalition formation is traditionally modeled using cooperative game theory, behavioral game theorists have repeatedly shown that outcomes predicted by game theory are different from those generated by actual human behavior. To further explore these differences, in a cooperative game theory context, we experiment to compare the outcomes resulting from human participants’ behavior to those generated by a cooperative game theory solution mechanism called the core partition. Our experiment uses an interactive simulation of a glove game, a particular type of cooperative game, to collect the participant’s decision choices and their resultant outcomes. Two different glove games are considered, …
Exploring Blockchain Adoption Supply Chains: Opportunities And Challenges,
2022
Old Dominion University
Exploring Blockchain Adoption Supply Chains: Opportunities And Challenges, Adrian V. Gheorghe, Omer F. Keskin, Farinaz Sabz Ali Pour
Engineering Management & Systems Engineering Faculty Publications
In modern supply chains, acquisition often occurs with the involvement of a network of organizations. The resilience, efficiency, and effectiveness of supply networks are crucial for the viability of acquisition. Disruptions in the supply chain require adequate communication infrastructure to ensure resilience. However, supply networks do not have a shared information technology infrastructure that ensures effective communication. Therefore decision-makers seek new methodologies for supply chain management resilience. Blockchain technology offers new decentralization and service delegation methods that can transform supply chains and result in a more flexible, efficient, and effective supply chain. This report presents a framework for the application …
Combining Green Metrics And Digital Twins For Sustainability Planning And Governance Of Smart Buildings And Cities,
2022
The MITRE Corporation & Old Dominion University
Combining Green Metrics And Digital Twins For Sustainability Planning And Governance Of Smart Buildings And Cities, Casey R. Corrado, Suzanne M. Delong, Emily G. Holt, Edward Y. Hua, Andreas Tolk
VMASC Publications
Creating a more sustainable world will require a coordinated effort to address the rise of social, economic, and environmental concerns resulting from the continuous growth of cities. Supporting planners with tools to address them is pivotal, and sustainability is one of the main objectives. Modeling and simulation augmenting digital twins can play an important role to implement these tools. Although various green best practices have been utilized over time and there are related attempts at measuring green success, works in the published literature tend to focus on addressing a single problem (e.g., energy efficiency), and a comprehensive approach that takes …
Exploring Cyber-Physical Systems’ Security Governance In The Oil And Gas Industry,
2022
Walden University
Exploring Cyber-Physical Systems’ Security Governance In The Oil And Gas Industry, Soliman Mahmoud
Walden Dissertations and Doctoral Studies
The Fourth Industrial Revolution, which utilizes modern communication-dependent technologies, including cyber-physical systems (CPS), has made exploration and production operations more efficient in the oil and gas industry. CPS in this industry should be secured against operational threats to prevent interruption of critical oil and gas supplies and services. However, these systems are vulnerable to cyberattacks, and many oil and gas companies have not incorporated effective cybersecurity measures into their corporate management strategies. This qualitative, multiple-case study, which was guided by the routine activity theory, explored how cybersecurity governance was applied to develop controls that stopped or mitigated the consequences of …
