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Articles 2641 - 2670 of 17318

Full-Text Articles in Computer Sciences

Agent-Based Ecosystem Simulation Research Under Forest Fire, Ying Li, Nisuo Du, Zhi Ouyang Jun 2023

Agent-Based Ecosystem Simulation Research Under Forest Fire, Ying Li, Nisuo Du, Zhi Ouyang

Journal of System Simulation

An Agent-based multi-species simulation model under forest fireis proposed to study the effect of forest fire on the balance of animal species population.By abstracting elements of each type of species and fire in the forest fire process as agents, the attributes and behavior rules of each type of agents according to the real characteristics of each type of species and forest fire are refined. ABM model is used to show the characteristics of multi-agent interaction in complex systems, and construct a multi-species forest ecological model and a forest fire model. On the basis of validating the rationality of …

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Opto-Mechanical-Thermal Coupling Analysis Method And Implementation Of High-Precision Optical System, Liang Zhao, Zhigang Zhang, Yao Sun Jun 2023

Opto-Mechanical-Thermal Coupling Analysis Method And Implementation Of High-Precision Optical System, Liang Zhao, Zhigang Zhang, Yao Sun

Journal of System Simulation

High-precision optical system is easy to be affected by space environment. Under the condition of high temperature, structural load, etc., the image quality of the optical system becomes poor, and the opto-mechanical-thermal coupling analysis is needed. Due to the independent development of the optical simulation, structure simulation, thermal simulation and others, the simulation data can not be effectively coupled and transferred.An interdisciplinary coupling analysis method is proposed, in which the integrated analysis idea is adopted and the polynomial fitting is used as the interface to solve the irregular deformation of optical element surface. Through the implement of the best …

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Research And Development Of Immersive Aero-Engine Scene Simulation System, Shun Yao, Zhongzhi Hu, Wenyu Cao, Jiali Yang Jun 2023

Research And Development Of Immersive Aero-Engine Scene Simulation System, Shun Yao, Zhongzhi Hu, Wenyu Cao, Jiali Yang

Journal of System Simulation

The research and development of aero-engines has the characteristics of high precision and interdiscipline. In order to reduce communication costs and to display the engine structure and the state of semi-physical simulator, by applying virtual reality technology,an immersive scene simulation system is built. By studying CAD data lightweight technology and physics-based real-time rendering technology,a rendering optimization method for similar object dynamic batching is proposed, which effectively improves the rendering frame rate. A dynamic parallax adjustment algorithm is proposed to solve the problem of dizziness when having a close look to stereoscopic images. The system achieves the …

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Neutrosophic Framework For Assessment Challenges In Smart Sustainable Cities Based On Iot To Better Manage Energy Resources And Decrease The Urban Environment's Ecological Impact, Samah Ibrahim Abdel Aal Jun 2023

Neutrosophic Framework For Assessment Challenges In Smart Sustainable Cities Based On Iot To Better Manage Energy Resources And Decrease The Urban Environment's Ecological Impact, Samah Ibrahim Abdel Aal

Neutrosophic Systems with Applications

Sustainable smart cities based on the Internet of Things (IoT) technology provide promising prospects for improving quality of life. However, in order to facilitate the widespread implementation of IoT-based smart city solutions, there is a need to concern about data privacy and security, standardization, interoperability, scalability, and sustainability. Reducing the environmental effect of urban activities, optimizing the management of energy resources, and designing novel services and solutions for inhabitants are all examples of how the smart city concept is inextricably linked to sustainability. There is a need to assess challenges in smart sustainable cities based on IoT. This paper is …

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Insect Classification And Explainability From Image Data Via Deep Learning Techniques, Tanvir Hossain Bhuiyan Jun 2023

Insect Classification And Explainability From Image Data Via Deep Learning Techniques, Tanvir Hossain Bhuiyan

USF Tampa Graduate Theses and Dissertations

Since the dawn of the Industrial Revolution, humanity has always tried to make labor more efficient and automated, and this trend is only continuing in the modern digital age. With the advent of artificial intelligence (AI) techniques in the latter part of the 20th century, the speed and scale with which AI has been leveraged to automate tasks defy human imagination. Many people deeply entrenched in the technology field are genuinely intrigued and concerned about how AI may change many of the ways in which humans have been living for millennia. Only time will provide the answers. This dissertation is …

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Neutrosophic Framework For Assessment Challenges In Smart Sustainable Cities Based On Iot To Better Manage Energy Resources And Decrease The Urban Environment's Ecological Impact, Samah Ibrahim Abdel Aal Jun 2023

Neutrosophic Framework For Assessment Challenges In Smart Sustainable Cities Based On Iot To Better Manage Energy Resources And Decrease The Urban Environment's Ecological Impact, Samah Ibrahim Abdel Aal

Neutrosophic Systems with Applications

Sustainable smart cities based on the Internet of Things (IoT) technology provide promising prospects for improving quality of life. However, in order to facilitate the widespread implementation of IoT-based smart city solutions, there is a need to concern about data privacy and security, standardization, interoperability, scalability, and sustainability. Reducing the environmental effect of urban activities, optimizing the management of energy resources, and designing novel services and solutions for inhabitants are all examples of how the smart city concept is inextricably linked to sustainability. There is a need to assess challenges in smart sustainable cities based on IoT. This paper is …

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Coordinating Tethered Autonomous Underwater Vehicles Towards Entanglement-Free Navigation, Abhishek Patil, Myoungkuk Park, Jungyun Bae Jun 2023

Coordinating Tethered Autonomous Underwater Vehicles Towards Entanglement-Free Navigation, Abhishek Patil, Myoungkuk Park, Jungyun Bae

Michigan Tech Publications, Part 1

This paper proposes an algorithm that provides operational strategies for multiple tethered autonomous underwater vehicle (T-AUV) systems for entanglement-free navigation. T-AUVs can perform underwater tasks under reliable communication and power supply, which is the most substantial benefit of their operation. Thus, if one can overcome the entanglement issues while utilizing multiple tethered vehicles, the potential applications of the system increase including ecosystem exploration, infrastructure inspection, maintenance, search and rescue, underwater construction, and surveillance. In this study, we focus on developing strategies for task allocation, path planning, and scheduling that ensure entanglement-free operations while considering workload balancing among the vehicles. We …

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An Electric Vehicle Analysis Model For Sustainable Environment In Devoicing Nationals, Nada A. Nabeeh, Karam M. Sallam, Ali Wagdy Mohamed Jun 2023

An Electric Vehicle Analysis Model For Sustainable Environment In Devoicing Nationals, Nada A. Nabeeh, Karam M. Sallam, Ali Wagdy Mohamed

Neutrosophic Systems with Applications

The usage of fossil fuels is regarded as the generation of energy alternative towards electric vehicles (EVs) in third-world nations for a cleaner transportation sector. The rapid development of EVs is the most effective solution, even if the short-term ecological benefits for third-world nations cannot cover the short-term expenses. Since ecological issues have opened the door for certain developing nations to catch up to the worldwide competition, it is important to weigh other options to bring EVs to the marketplace. Hence, the study proposes a model of neutrosophic set combined with entropy to deal with uncertain cases. The proposed model …

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Adversary Aware Continual Learning, Muhammad Umer Jun 2023

Adversary Aware Continual Learning, Muhammad Umer

Theses and Dissertations

Continual learning approaches are useful as they help the model to learn new information (classes) sequentially, while also retaining the previously acquired information (classes). However, these approaches are adversary agnostic, i.e., they do not consider the possibility of malicious attacks. In this dissertation, we have demonstrated that continual learning approaches are extremely vulnerable to the adversarial backdoor attacks, where an intelligent adversary can introduce small amount of misinformation to the model in the form of imperceptible backdoor pattern during training to cause deliberate forgetting of a specific class at test time. We then propose a novel defensive framework to counter …

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An Electric Vehicle Analysis Model For Sustainable Environment In Devoicing Nationals, Nada A. Nabeeh, Karam M. Sallam, Ali Wagdy Mohamed Jun 2023

An Electric Vehicle Analysis Model For Sustainable Environment In Devoicing Nationals, Nada A. Nabeeh, Karam M. Sallam, Ali Wagdy Mohamed

Neutrosophic Systems with Applications

The usage of fossil fuels is regarded as the generation of energy alternative towards electric vehicles (EVs) in third-world nations for a cleaner transportation sector. The rapid development of EVs is the most effective solution, even if the short-term ecological benefits for third-world nations cannot cover the short-term expenses. Since ecological issues have opened the door for certain developing nations to catch up to the worldwide competition, it is important to weigh other options to bring EVs to the marketplace. Hence, the study proposes a model of neutrosophic set combined with entropy to deal with uncertain cases. The proposed model …

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Poly-Gan: Regularizing Polygons With Generative Adversarial Networks, Lasith Niroshan, James Carswell Jun 2023

Poly-Gan: Regularizing Polygons With Generative Adversarial Networks, Lasith Niroshan, James Carswell

Conference Papers

Regularizing polygons involves simplifying irregular and noisy shapes of built environment objects (e.g. buildings) to ensure that they are accurately represented using a minimum number of vertices. It is a vital processing step when creating/transmitting online digital maps so that they occupy minimal storage space and bandwidth. This paper presents a data-driven and Deep Learning (DL) based approach for regularizing OpenStreetMap building polygon edges. The study introduces a building footprint regularization technique (Poly-GAN) that utilises a Generative Adversarial Network model trained on irregular building footprints and OSM vector data. The proposed method is particularly relevant for map features …

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Neuroevolution Application To Collaborative And Heuristics-Based Connected And Autonomous Vehicle Cohort Simulation At Uncontrolled Intersection, Frederic Jacquelin, Jungyun Bae, Bo Chen, Darrell Robinette Jun 2023

Neuroevolution Application To Collaborative And Heuristics-Based Connected And Autonomous Vehicle Cohort Simulation At Uncontrolled Intersection, Frederic Jacquelin, Jungyun Bae, Bo Chen, Darrell Robinette

Michigan Tech Publications

Artificial intelligence is gaining tremendous attractiveness and showing great success in solving various problems, such as simplifying optimal control derivation. This work focuses on the application of Neuroevolution to the control of Connected and Autonomous Vehicle (CAV) cohorts operating at uncontrolled intersections. The proposed method implementation’s simplicity, thanks to the inclusion of heuristics and effective real-time performance are demonstrated. The resulting architecture achieves nearly ideal operating conditions in keeping the average speeds close to the speed limit. It achieves twice as high mean speed throughput as a controlled intersection, hence enabling lower travel time and mitigating energy inefficiencies from stop-and-go …

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Optimal Domain-Partitioning Algorithm For Real-Life Transportation Networks And Finite Element Meshes, Jimesh Bhagatji, Sharanabasaweshwara Asundi, Eric Thompson, Duc T. Nguyen Jun 2023

Optimal Domain-Partitioning Algorithm For Real-Life Transportation Networks And Finite Element Meshes, Jimesh Bhagatji, Sharanabasaweshwara Asundi, Eric Thompson, Duc T. Nguyen

Civil & Environmental Engineering Faculty Publications

For large-scale engineering problems, it has been generally accepted that domain-partitioning algorithms are highly desirable for general-purpose finite element analysis (FEA). This paper presents a heuristic numerical algorithm that can efficiently partition any transportation network (or any finite element mesh) into a specified number of subdomains (usually depending on the number of parallel processors available on a computer), which will result in “minimising the total number of system BOUNDARY nodes” (as a primary criterion) and achieve “balancing work loads” amongst the subdomains (as a secondary criterion). The proposed seven-step heuristic algorithm (with enhancement features) is based on engineering common sense …

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Novel Approach For Non-Invasive Prediction Of Body Shape And Habitus, Emma Young Jun 2023

Novel Approach For Non-Invasive Prediction Of Body Shape And Habitus, Emma Young

Electronic Theses and Dissertations

While marker-based motion capture remains the gold standard in measuring human movement, accuracy is influenced by soft-tissue artifacts, particularly for subjects with high body mass index (BMI) where markers are not placed close to the underlying bone. Obesity influences joint loads and motion patterns, and BMI may not be sufficient to capture the distribution of a subject’s weight or to differentiate differences between subjects. Subjects in need of a joint replacement are more likely to have mobility issues or pain, which prevents exercise. Obesity also increases the likelihood of needing a total joint replacement. Accurate movement data for subjects with …

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Patient Movement Monitoring Based On Imu And Deep Learning, Mohsen Sharifi Renani Jun 2023

Patient Movement Monitoring Based On Imu And Deep Learning, Mohsen Sharifi Renani

Electronic Theses and Dissertations

Osteoarthritis (OA) is the leading cause of disability among the aging population in the United States and is frequently treated by replacing deteriorated joints with metal and plastic components. Developing better quantitative measures of movement quality to track patients longitudinally in their own homes would enable personalized treatment plans and hasten the advancement of promising new interventions. Wearable sensors and machine learning used to quantify patient movement could revolutionize the diagnosis and treatment of movement disorders. The purpose of this dissertation was to overcome technical challenges associated with the use of wearable sensors, specifically Inertial Measurement Units (IMUs), as a …

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Ocapo: Occupancy-Aware, Pdc Control For Open-Plan, Shared Workspaces, Anaradha Ravi, Archan Misra Jun 2023

Ocapo: Occupancy-Aware, Pdc Control For Open-Plan, Shared Workspaces, Anaradha Ravi, Archan Misra

Research Collection School Of Computing and Information Systems

Passive Displacement Cooling (PDC) has gained popularity as a means of significantly reducing building energy consumption overheads, especially in tropical climates. PDC eliminates the use of mechanical fans, instead using chilled-water heat exchangers to perform convective cooling. In this paper, we evaluate the impact of different parameters affecting occupant comfort in a 1000m2 open-floor area (consisting of multiple zones) of a ZEB (Zero Energy Building) deployed with PDC units and tackle the problem of setting the temperature setpoint of the PDC units to assure occupant thermal comfort. We tackle two key practical challenges: (a) the zone-level (i.e., occupant-experienced) temperature differs …

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A Mixed-Integer Linear Programming Reduction Of Disjoint Bilinear Programs Via Symbolic Variable Elimination, Jihwan Jeong, Scott Sanner, Akshat Kumar Jun 2023

A Mixed-Integer Linear Programming Reduction Of Disjoint Bilinear Programs Via Symbolic Variable Elimination, Jihwan Jeong, Scott Sanner, Akshat Kumar

Research Collection School Of Computing and Information Systems

A disjointly constrained bilinear program (DBLP) has various practical and industrial applications, e.g., in game theory, facility location, supply chain management, and multi-agent planning problems. Although earlier work has noted the equivalence of DBLP and mixed-integer linear programming (MILP) from an abstract theoretical perspective, a practical and exact closed-form reduction of a DBLP to a MILP has remained elusive. Such explicit reduction would allow us to leverage modern MILP solvers and techniques along with their solution optimality and anytime approximation guarantees. To this end, we provide the first constructive closed-form MILP reduction of a DBLP by extending the technique of …

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Neutrosophic Mcdm Methodology For Risk Assessment Of Autonomous Underwater Vehicles, Shimaa S. Mohamed, Ahmed Abdel-Monem, Alshaimaa A. Tantawy May 2023

Neutrosophic Mcdm Methodology For Risk Assessment Of Autonomous Underwater Vehicles, Shimaa S. Mohamed, Ahmed Abdel-Monem, Alshaimaa A. Tantawy

Neutrosophic Systems with Applications

Due to its usefulness in several industries and the military, researchers have concentrated on developing autonomous underwater vehicles (AUVs). However, AUV navigation continues to be a difficult challenge to solve owing to the variety of underwater settings. The usage of AUVs, or autonomous underwater vehicles, is not without dangers like malfunction, ecological risks, loss of communications, cybersecurity risks, collisions, and others. There are many criteria to assess these risks technical, operational, economic, and regulatory. So, the methods of multi-criteria decision-making (MCDM) is used to deal with these various criteria. The analytical hierarchy process (AHP) method is an MCDM methodology, that …

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Neutrosophic Mcdm Methodology For Risk Assessment Of Autonomous Underwater Vehicles, Shimaa S. Mohamed, Ahmed Abdel-Monem, Alshaimaa A. Tantawy May 2023

Neutrosophic Mcdm Methodology For Risk Assessment Of Autonomous Underwater Vehicles, Shimaa S. Mohamed, Ahmed Abdel-Monem, Alshaimaa A. Tantawy

Neutrosophic Systems with Applications

Due to its usefulness in several industries and the military, researchers have concentrated on developing autonomous underwater vehicles (AUVs). However, AUV navigation continues to be a difficult challenge to solve owing to the variety of underwater settings. The usage of AUVs, or autonomous underwater vehicles, is not without dangers like malfunction, ecological risks, loss of communications, cybersecurity risks, collisions, and others. There are many criteria to assess these risks technical, operational, economic, and regulatory. So, the methods of multi-criteria decision-making (MCDM) is used to deal with these various criteria. The analytical hierarchy process (AHP) method is an MCDM methodology, that …

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Mining Themes In Clinical Notes To Identify Phenotypes And To Predict Length Of Stay In Patients Admitted With Heart Failure, Ankita Agarwal, Tanvi Banerjee, William Romine, Krishnaprasad Thirunarayan, Lingwei Chen, Mia Cajita May 2023

Mining Themes In Clinical Notes To Identify Phenotypes And To Predict Length Of Stay In Patients Admitted With Heart Failure, Ankita Agarwal, Tanvi Banerjee, William Romine, Krishnaprasad Thirunarayan, Lingwei Chen, Mia Cajita

Computer Science and Engineering Faculty Publications

Heart failure is a syndrome which occurs when the heart is not able to pump blood and oxygen to support other organs in the body. Identifying the underlying themes in the diagnostic codes and procedure reports of patients admitted for heart failure could reveal the clinical phenotypes associated with heart failure and to group patients based on their similar characteristics which could also help in predicting patient outcomes like length of stay. These clinical phenotypes usually have a probabilistic latent structure and hence, as there has been no previous work on identifying phenotypes in clinical notes of heart failure patients …

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Energy Efficiency And Material Cost Savings By Evolution Of Solar Panels Used In Photovoltaic Systems Under Neutrosophic Model, Ahmed Sleem, Ibrahim Elhenawy May 2023

Energy Efficiency And Material Cost Savings By Evolution Of Solar Panels Used In Photovoltaic Systems Under Neutrosophic Model, Ahmed Sleem, Ibrahim Elhenawy

Neutrosophic Systems with Applications

Traditional applications of solar panels have been limited to smaller-scale energy production, such as that required by single houses or apartment complexes. Researchers from all around the globe have been working together to develop creative, efficient goods, increase the energy efficiency of solar panels, and build new, ground-breaking practices using photovoltaic system design. Solar photovoltaic (PV) system planning demands a strategic decision-making approach to socioeconomic growth in many nations due to the rising understanding of the financial, social, and ecological aspects. The primary goal of this study is to provide a novel, adaptable method of Multi-Criteria Decision Making (MCDM) for …

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Energy Efficiency And Material Cost Savings By Evolution Of Solar Panels Used In Photovoltaic Systems Under Neutrosophic Model, Ahmed Sleem, Ibrahim Elhenawy May 2023

Energy Efficiency And Material Cost Savings By Evolution Of Solar Panels Used In Photovoltaic Systems Under Neutrosophic Model, Ahmed Sleem, Ibrahim Elhenawy

Neutrosophic Systems with Applications

Traditional applications of solar panels have been limited to smaller-scale energy production, such as that required by single houses or apartment complexes. Researchers from all around the globe have been working together to develop creative, efficient goods, increase the energy efficiency of solar panels, and build new, ground-breaking practices using photovoltaic system design. Solar photovoltaic (PV) system planning demands a strategic decision-making approach to socioeconomic growth in many nations due to the rising understanding of the financial, social, and ecological aspects. The primary goal of this study is to provide a novel, adaptable method of Multi-Criteria Decision Making (MCDM) for …

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Simulation Of Real-Time Path Planning And Formation Control For Unmanned Surface Vessel, Dalei Song, Wenhao Gan, Yingzhi Xu, Xiuqing Qu, Jiangli Cao May 2023

Simulation Of Real-Time Path Planning And Formation Control For Unmanned Surface Vessel, Dalei Song, Wenhao Gan, Yingzhi Xu, Xiuqing Qu, Jiangli Cao

Journal of System Simulation

Abstract: Safety and collision-free navigation are the basis of normal navigation of an unmanned surface vessel. The high-fidelity virtual ocean is constructed by using Unity3D.On the basis of the vessel modeling, a real-time path planning and formation control method for unknown complex environments is proposed. Firstly, the local environment information is obtained by the laser sensor. Then the real-time local path planning is completed by combining A-star and route-thinning methods under the replanning strategy. In addition, formation control is carried out based on the leader-follower strategy and consistency method, and the artificial potential field …

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Research On Optimal Scheduling Of Microgrid Based On Nbbo Algorithm, Lisheng Wei, Benben Yang, Ruixia Sun May 2023

Research On Optimal Scheduling Of Microgrid Based On Nbbo Algorithm, Lisheng Wei, Benben Yang, Ruixia Sun

Journal of System Simulation

Abstract: In view of the economic and environmental collaborative optimization of a microgrid with a micro gas turbine, power to gas(P2G) system with the ability to abandon wind and light for consumption and capture carbon is introduced, and a microgrid optimal scheduling model with P2G system based on novel biogeography-based optimization(NBBO) algorithm is proposed. The microgrid model with the P2G system is constructed, and the working principle of the main equipment is analyzed. The reserve capacity of a wind turbine is introduced to reduce the influence of the randomness of wind power …

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Deep Reinforcement Learning-Based Control Strategy For Boost Converter, Yuxuan Dai, Chenggang Cui May 2023

Deep Reinforcement Learning-Based Control Strategy For Boost Converter, Yuxuan Dai, Chenggang Cui

Journal of System Simulation

Abstract: In view of the problems of model uncertainty and nonlinearity in bus voltage stability control of Boost converter, an intelligent control strategy based on model-free deep reinforcement learning(RL) is proposed. RL double DQN(DDQN) algorithm and deep deterministic policy gradient(DDPG) algorithm are used, and the Boost converter controller is designed. The state, action space, reward function, and neural network are also designed to improve the dynamic performance of the controller. The joint simulation of the Boost converter model and RL agent is realized by RL modelica(RLM …

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Point Cloud Registration Method Based On Improved Covariance Matrix Descriptor, Yuan Zhang, Haoyu Han, Xie Han, Jiaxu Fu May 2023

Point Cloud Registration Method Based On Improved Covariance Matrix Descriptor, Yuan Zhang, Haoyu Han, Xie Han, Jiaxu Fu

Journal of System Simulation

Abstract: Point cloud registration is a key part of the digital protection of cultural relics. Improving registration accuracy and noise resistance is the main goal of point cloud registration for cultural relics. In order to solve this problem, a three-dimensional (3D) point cloud registration method based on a covariance matrix descriptor is proposed. The tensor voting method is used to eliminate the noise points, and the internal shape signature method is used to extract the key points from the point cloud after removing the noise. Then, the neighborhood information is constructed for the extracted key points, …

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Outlier Detection During Thermal Processes Based On Improved Gaussian Mixture Model, Zheng Wu, Yue Zhang, Ze Dong May 2023

Outlier Detection During Thermal Processes Based On Improved Gaussian Mixture Model, Zheng Wu, Yue Zhang, Ze Dong

Journal of System Simulation

Abstract: Abnormal data detection during thermal processes is the basis for performing system modeling, control, and optimization and constitutes an important part of data processing. In this paper, an unsupervised outlier detection algorithm during thermal processes based on an improved Gaussian mixture model is proposed. The algorithm captures a class of data clusters under specific working conditions by using Gaussian components in each dimension, modifies the posterior probability density of the traditional model by adding penalty constraint factors to penalize the false detection and missed detection items, and identifies abnormal data according to the correlation differences with the …

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Improved Social Force Model Based On Enhancing Psych Behavioral Heterogeneity, Yandong Liu, Gaoxiang Huang, Wen Chen May 2023

Improved Social Force Model Based On Enhancing Psych Behavioral Heterogeneity, Yandong Liu, Gaoxiang Huang, Wen Chen

Journal of System Simulation

Abstract: Simulating the evacuation behavior of people under anxiety is of great significance for solving the kinematic problems such as escape. At present, most at home and abroad studies consider the anxiety factors as the only medium of population evacuation without considering how external key factors affect anxiety factors in such emergency environments. The improved social force model is proposed, combined with Agent-based stampede risk assessment, the influence of key environmental variables on the anxiety factor is quantified. The psychological force parameters are introduced, and the impact of the anxiety factor on the actual evacuation process is applied to the …

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Simulation And Optimization Of Integrated Production Logistics System Of Underground Coal Mining, Dressing, And Backfilling, Xiangqian Wang, Puhao Guo, Xiangrui Meng May 2023

Simulation And Optimization Of Integrated Production Logistics System Of Underground Coal Mining, Dressing, And Backfilling, Xiangqian Wang, Puhao Guo, Xiangrui Meng

Journal of System Simulation

Abstract: In order to study the green mining mode of coal, the bottleneck problem in the integrated production logistics system of underground coal mining, dressing, and backfilling under the goal of achieving the basic production capacity target is explored, so as to promote the coordinated and efficient logistics transportation of underground coal and gangue. A mine in Shanxi is selected as the prototype, and the queuing theory is adopted to analyze the operation process of the integrated coal production logistics system. A discrete event model is established with the help of Anylogic simulation software for related experimental optimization …

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Research On Collaborative Task Allocation Method Of Multiple Uavs Based On Blockchain, Shuangcheng Niu, Yuqiang Jin, Kunhu Kou May 2023

Research On Collaborative Task Allocation Method Of Multiple Uavs Based On Blockchain, Shuangcheng Niu, Yuqiang Jin, Kunhu Kou

Journal of System Simulation

Abstract: The autonomous collaborative control of a multi-unmanned aerial vehicle (UAV) system lacks a unified underlying technology platform and faces single point failure and information security threats. In order to solve these problems, an idea to build collaborative task planning platforms based on blockchain technology is proposed. With thecollaborative task allocation of multiple UAVs as research objects, an online, safe, high-efficiency, and real-time task allocation method is designed. The contract network task allocation algorithm is described as a smart contract, and system consensus is reached based on the blockchain consensus algorithm. In addition, …

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