Open Access. Powered by Scholars. Published by Universities.®
- Institution
-
- China Simulation Federation (3880)
- TÜBİTAK (3106)
- Wright State University (1814)
- University of Nebraska - Lincoln (1069)
- University of Texas at El Paso (859)
-
- Washington University in St. Louis (733)
- Technological University Dublin (731)
- California Polytechnic State University, San Luis Obispo (722)
- Brigham Young University (641)
- Old Dominion University (579)
- Embry-Riddle Aeronautical University (563)
- Singapore Management University (546)
- Universitas Indonesia (444)
- San Jose State University (439)
- Santa Clara University (422)
- Air Force Institute of Technology (414)
- Marquette University (412)
- University of South Carolina (320)
- California State University, San Bernardino (288)
- University of Central Florida (271)
- Portland State University (266)
- Chulalongkorn University (243)
- Al Iraqia University (235)
- Purdue University (218)
- University of South Florida (218)
- University of Arkansas, Fayetteville (209)
- University of Nevada, Las Vegas (191)
- New Jersey Institute of Technology (185)
- Nova Southeastern University (183)
- University of Dayton (166)
- Keyword
-
- Machine learning (440)
- Computer Science (385)
- Deep learning (347)
- Department of Computer Science and Engineering (319)
- Machine Learning (288)
-
- Engineering (274)
- Simulation (237)
- Robotics (233)
- Security (183)
- Artificial intelligence (174)
- Deep Learning (172)
- Optimization (170)
- Computer Engineering (168)
- Classification (163)
- College of Engineering and Computer Science (157)
- Newsletters (157)
- Science news (157)
- Technical writing (157)
- Cybersecurity (154)
- Artificial Intelligence (148)
- Computer vision (141)
- Computer Science and Engineering (137)
- Genetic algorithm (119)
- Blockchain (99)
- Internet (97)
- Virtual reality (97)
- Path planning (94)
- Data mining (93)
- Clustering (91)
- Privacy (91)
- Publication Year
- Publication
-
- Journal of System Simulation (3880)
- Turkish Journal of Electrical Engineering and Computer Sciences (3106)
- Computer Science & Engineering Syllabi (1312)
- Departmental Technical Reports (CS) (760)
- Theses and Dissertations (730)
-
- All Computer Science and Engineering Research (683)
- International Congress on Environmental Modelling and Software (629)
- Research Collection School Of Computing and Information Systems (511)
- Department of Electrical and Computer Engineering: Faculty Publications (496)
- Makara Journal of Technology (436)
- Electrical and Computer Engineering Faculty Research and Publications (389)
- Browse all Theses and Dissertations (342)
- Electronic Theses and Dissertations (342)
- Dissertations (340)
- Faculty Publications (321)
- Journal of Digital Forensics, Security and Law (299)
- Computer Science and Engineering Senior Theses (298)
- Master's Theses (289)
- Computer Engineering (282)
- Chulalongkorn University Theses and Dissertations (Chula ETD) (242)
- Iraqi Journal for Computer Science and Mathematics (235)
- Master's Projects (220)
- School of Computing: Dissertations, Theses, and Student Research (206)
- Electrical and Computer Engineering Faculty Publications (204)
- Electrical & Computer Engineering Theses & Dissertations (193)
- Conference papers (178)
- Publications (169)
- BITs and PCs Newsletter (157)
- USF Tampa Graduate Theses and Dissertations (157)
- Journal of International Technology and Information Management (153)
- Publication Type
- File Type
Articles 4081 - 4110 of 25653
Full-Text Articles in Engineering
Digital Game-Based Approach To Math Learning For Students, Gul Ayaz, Katherine Smith
Digital Game-Based Approach To Math Learning For Students, Gul Ayaz, Katherine Smith
Modeling, Simulation and Visualization Student Capstone Conference
Mathematics is an important subject that is pervasive across many disciplines. It is also a subject that has proven to be challenging to both teach and learn. Students face many challenges with learning math such as a lack of motivation and anxiety. To address these challenges, game-based learning has become a popular approach to stimulate students and create a more positive classroom environment. It can serve as an alternative or supplement to traditional teaching and can better engage students while developing a positive attitude toward learning. The use of games in a classroom can create a more exciting and engaging …
Gpu Utilization: Predictive Sarimax Time Series Analysis, Dorothy Dorie Parry
Gpu Utilization: Predictive Sarimax Time Series Analysis, Dorothy Dorie Parry
Modeling, Simulation and Visualization Student Capstone Conference
This work explores collecting performance metrics and leveraging the output for prediction on a memory-intensive parallel image classification algorithm - Inception v3 (or "Inception3"). Experimental results were collected by nvidia-smi on a computational node DGX-1, equipped with eight Tesla V100 Graphic Processing Units (GPUs). Time series analysis was performed on the GPU utilization data taken, for multiple runs, of Inception3’s image classification algorithm (see Figure 1). The time series model applied was Seasonal Autoregressive Integrated Moving Average Exogenous (SARIMAX).
Behind Derogatory Migrants' Terms For Venezuelan Migrants: Xenophobia And Sexism Identification With Twitter Data And Nlp, Joseph Martínez, Melissa Miller-Felton, Jose Padilla, Erika Frydenlund
Behind Derogatory Migrants' Terms For Venezuelan Migrants: Xenophobia And Sexism Identification With Twitter Data And Nlp, Joseph Martínez, Melissa Miller-Felton, Jose Padilla, Erika Frydenlund
Modeling, Simulation and Visualization Student Capstone Conference
The sudden arrival of many migrants can present new challenges for host communities and create negative attitudes that reflect that tension. In the case of Colombia, with the influx of over 2.5 million Venezuelan migrants, such tensions arose. Our research objective is to investigate how those sentiments arise in social media. We focused on monitoring derogatory terms for Venezuelans, specifically veneco and veneca. Using a dataset of 5.7 million tweets from Colombian users between 2015 and 2021, we determined the proportion of tweets containing those terms. We observed a high prevalence of xenophobic and defamatory language correlated with the …
An Algorithm For Finding Data Dependencies In An Event Graph, Erik J. Jensen
An Algorithm For Finding Data Dependencies In An Event Graph, Erik J. Jensen
Modeling, Simulation and Visualization Student Capstone Conference
This work presents an algorithm for finding data dependencies in a discrete-event simulation system, from the event graph of the system. The algorithm can be used within a parallel discrete-event simulation. Also presented is an experimental system and event graph, which is used for testing the algorithm. Results indicate that the algorithm can provide information about which vertices in the experimental event graph can affect other vertices, and the minimum amount of time in which this interference can occur.
Automatic Generation Of Virtual Work Guide For Complex Procedures: A Case, Shan Liu, Yuzhong Shen
Automatic Generation Of Virtual Work Guide For Complex Procedures: A Case, Shan Liu, Yuzhong Shen
Modeling, Simulation and Visualization Student Capstone Conference
Practical work guides for complex procedures are significant and highly affect the efficiency and accuracy of on-site users. This paper presents a technique to generate virtual work guides automatically for complex procedures. Firstly, the procedure information is extracted from the electronic manual in PDF format. And then, the extracted procedure steps are mapped to the virtual model parts in preparation for animation between adjacent steps. Next, smooth animations of the procedure are generated based on a 3D natural cubic spline curve to improve the spatial ability of the work guide. In addition, each step's annotation is automatically adjusted to improve …
U-Net Based Multiclass Semantic Segmentation For Natural Disaster Based Satellite Imagery, Nishat Ara Nipa
U-Net Based Multiclass Semantic Segmentation For Natural Disaster Based Satellite Imagery, Nishat Ara Nipa
Modeling, Simulation and Visualization Student Capstone Conference
Satellite image analysis of natural disasters is critical for effective emergency response, relief planning, and disaster prevention. Semantic segmentation is believed to be on of the best techniques to capture pixelwise information in computer vision. In this work we will be using a U-Net architecture to do a three class semantic segmentation for the Xview2 dataset to capture the level of damage caused by different natural disaster which is beyond the visual scope of human eyes.
Simulating Function Generators And Oscilloscopes In A Virtual Laboratory Environment, Yiyang Li, Yuzhong Shen, Charles I. Sukenik
Simulating Function Generators And Oscilloscopes In A Virtual Laboratory Environment, Yiyang Li, Yuzhong Shen, Charles I. Sukenik
Modeling, Simulation and Visualization Student Capstone Conference
This paper discusses the development of a virtual laboratory for simulating electronic instruments commonly used in science and engineering courses, such as function generators and digital storage oscilloscopes. Mathematical equations are used to represent continuous signals and ensure signal integrity, while C# delegates are adopted to enable communication between simulated devices. The approach allows for loose coupling between software components and high cohesion of individual components, and can be applied to other virtual laboratory developments. The virtual laboratory provides a means for students to gain hands-on experience with electronic instruments and improve their understanding of theoretical concepts.
Assessing Frustration Towards Venezuelan Migrants In Columbia: Path Analysis On Newspaper Coded Data, Brian Llinás, Guljannat Huseynli, Erika Frydenlund, Katherine Palacia, Jose Padilla
Assessing Frustration Towards Venezuelan Migrants In Columbia: Path Analysis On Newspaper Coded Data, Brian Llinás, Guljannat Huseynli, Erika Frydenlund, Katherine Palacia, Jose Padilla
Modeling, Simulation and Visualization Student Capstone Conference
This study analyzes the impact of Venezuelan migrants on local frustration levels in Colombia. The study found a relationship between the influx of Venezuelan migrants and the level of frustration among locals towards migrants, infrastructure, government, and geopolitics. Additionally, we identified that frustration types have an impact on other frustrations. The study used articles from a national newspaper in Colombia from 2015 to 2020. News articles were coded during a previous study qualitatively and categorized into frustration types. The code frequencies were then used as variables in this study. We used path modeling to statistically study the relationship between dependent …
Lidar Buoy Detection For Autonomous Marine Vessel Using Pointnet Classification, Christopher Adolphi, Dorothy Dorie Parry, Yaohang Li, Masha Sosonkina, Ahmet Saglam, Yiannis E. Papelis
Lidar Buoy Detection For Autonomous Marine Vessel Using Pointnet Classification, Christopher Adolphi, Dorothy Dorie Parry, Yaohang Li, Masha Sosonkina, Ahmet Saglam, Yiannis E. Papelis
Modeling, Simulation and Visualization Student Capstone Conference
Maritime autonomy, specifically the use of autonomous and semi-autonomous maritime vessels, is a key enabling technology supporting a set of diverse and critical research areas, including coastal and environmental resilience, assessment of waterway health, ecosystem/asset monitoring and maritime port security. Critical to the safe, efficient and reliable operation of an autonomous maritime vessel is its ability to perceive on-the-fly the external environment through onboard sensors. In this paper, buoy detection for LiDAR images is explored by using several tools and techniques: machine learning methods, Unity Game Engine (herein referred to as Unity) simulation, and traditional image processing. The Unity Game …
Implementation Of Static Rfid Landmarks In Slam For Planogram Compliance, Brennan L. Drake
Implementation Of Static Rfid Landmarks In Slam For Planogram Compliance, Brennan L. Drake
Honors College Theses
Autonomous robotic systems are becoming increasingly prevalent in everyday life and exhibit robust solutions in a wide range of applications. They face many obstacles with the foremost of which being SLAM, or Simultaneous Localization and Mapping, that encompasses both creation of the map of an unknown environment and localization of the robot in said environment. In this experiment, researchers propose the use of RFID tags in a semi-dynamic commercial environment to provide concrete landmarks for localization and mapping in pursuit of increased locational certainty. With this obtained, the ultimate goal of the research is to construct a robotics platform for …
Research On Construction Method Of Ubiquitous Operating System Open Source Ecosystem Based On Internet Of Everything, Meng Wang, Weidong Li
Research On Construction Method Of Ubiquitous Operating System Open Source Ecosystem Based On Internet Of Everything, Meng Wang, Weidong Li
Bulletin of Chinese Academy of Sciences (Chinese Version)
Building an independent, healthy, and sustainable open source ecosystem is a key link in the development and application of ubiquitous operating system. Aiming at the Internet of Everything, combined with the new characteristics of ubiquitous operating system, this study summarizes the constituent elements and system model of ubiquitous operating system open source ecosystem, and puts forward the construction method of ubiquitous operating system open source ecosystem. This study provides new ideas to promote the iterative innovation of ubiquitous operating system, integrate the isolated island of ubiquitous operating system open source ecosystem, and promote the preliminary practice and collaborative development of …
From Policy Promotion To Research Output: Brief Analysis Of Technical Challenges Of Hospital-Led Artificial Intelligence Research, Yu Zhuang, Cheng Zhou
From Policy Promotion To Research Output: Brief Analysis Of Technical Challenges Of Hospital-Led Artificial Intelligence Research, Yu Zhuang, Cheng Zhou
Bulletin of Chinese Academy of Sciences (Chinese Version)
In recent years, artificial intelligence has become a key direction of medical and health-related research and a hot spot of international competition. In order to investigate the current situation and challenges in hospital-led artificial intelligence researched, this study selects 14 national pilot hospitals to promote the high-quality development of public hospitals as samples, adopts a combination of quantitative and qualitative methods, analyzes the research articles related to artificial intelligence published by the sample hospitals in recent years, and analyzes the technical challenges in the hospital-led artificial intelligence research. The results show that although the number of hospital-led artificial intelligence research …
Designing An Equity-Centered Framework And Crosswalk For Integrated Elementary Computer Science Curriculum And Instruction, Carla Strickland, Andrea Ramírez-Salgado, Lauren Weisberg, Latoya Chandler, Jeanne Di Domenico, Elizabeth M. Lehman, Maya Israel
Designing An Equity-Centered Framework And Crosswalk For Integrated Elementary Computer Science Curriculum And Instruction, Carla Strickland, Andrea Ramírez-Salgado, Lauren Weisberg, Latoya Chandler, Jeanne Di Domenico, Elizabeth M. Lehman, Maya Israel
Journal of Computer Science Integration
As computer science (CS) education becomes more prevalent in K-12 instruction, it is critical for educators, researchers, and curriculum developers to identify culturally responsive and pedagogically inclusive approaches that can increase participation, access, and feelings of belonging for students from historically marginalized communities. In response, we developed an equity-centered curricular framework and illustrative crosswalk that synchronizes three distinct pedagogical approaches: culturally responsive pedagogy (CRP), Universal Design for Learning (UDL), and project-based learning (PBL). We describe the framework’s theoretical underpinnings and explain how this framework informed the development of an integrated elementary science+CS curricular unit and provide examples of its implementation. …
Proposed Mitigation Framework For The Internet Of Insecure Things, Mahmoud M. Elgindy, Sally M. Elghamrawy, Ali I. El-Desouky
Proposed Mitigation Framework For The Internet Of Insecure Things, Mahmoud M. Elgindy, Sally M. Elghamrawy, Ali I. El-Desouky
Mansoura Engineering Journal
Intrusion detection systems IDS are increasingly utilizing machine learning methods. IDSs are important tools for ensuring the security of network data and resources. The Internet of Things (IoT) is an expanding network of intelligent machines and sensors. However, they are vulnerable to attackers because of the ubiquitous and extensive IoT networks. Datasets from intrusion detection systems (IDS) have been analyzed deep learning methods such as Bidirectional long-short term memory (BiLSTM). This research presents an BiLSTM intrusion detection framework with Principal Component Analysis PCA (PCA-LSTM-IDS). The PCA-LSTM-IDS is comprised of two layers: extracting layer which using PCA, and the anomaly BiLSTM …
Claw Hand Activity, Admin Stem For Success, Natalie Wilson
Claw Hand Activity, Admin Stem For Success, Natalie Wilson
STEM for Success Showcase
Activity plan where students practice coding principles by programming the actions of a claw hand
Development Of A Smart Waste Management System For City Application, Lawrence D. Fraction
Development Of A Smart Waste Management System For City Application, Lawrence D. Fraction
Morehead State Theses and Dissertations
A thesis presented to the faculty of the Elmer R. Smith College of Business and Technology Morehead State University in partial fulfillment of the requirements for the Degree Master of Science by Lawrence D. Fraction on April 14, 2023.
Role Of Ai In Threat Detection And Zero-Day Attacks, Kelly Morgan
Role Of Ai In Threat Detection And Zero-Day Attacks, Kelly Morgan
Cybersecurity Undergraduate Research Showcase
Cybercrime and attack methods have been steadily increasing since the 2019 pandemic. In the years following 2019, the number of victims and attacks per hour rapidly increased as businesses and organizations transitioned to digital environments for business continuity amidst lockdowns. In most scenarios cybercriminals continued to use conventional attack methods and known vulnerabilities that would cause minimal damage to an organization with a robust cyber security posture. However, zero-day exploits have skyrocketed across all industries with an increasingly growing technological landscape encompassing internet of things (IoT), cloud hosting, and more advanced mobile technologies. Reports by Mandiant Threat Intelligence (2022) concluded …
Lack Of Black Female Diversity Within The Cybersecurity Workforce, Eric Preston
Lack Of Black Female Diversity Within The Cybersecurity Workforce, Eric Preston
Cybersecurity Undergraduate Research Showcase
Cybersecurity methods, strategies, and programs for protecting computers and electronic devices have become critically important in all aspects of the technological infrastructure. However, while this is a vastly growing field that has a large workforce, it suffers from a lack of representation, specifically for Black/African American females. This study examines the barriers that prevent Black women from having representation within the cybersecurity workforce and solutions that address them. Some barriers noted include a lack of role models and resources, historical discrimination and systemic barriers, and cultural norms. Additionally, implications created by these barriers include less diversity, a lack of career …
A New Framework To Assess The Individual Fairness Of Probabilistic Classifiers, Muhammad Fawad Akbar Khan
A New Framework To Assess The Individual Fairness Of Probabilistic Classifiers, Muhammad Fawad Akbar Khan
Student Research Symposium
Fairness in machine learning has become a global concern due to the predominance of ML in automated decision-making systems. In comparison to group fairness, individual fairness, which aspires that similar individuals should be treated similarly, has received limited attention due to some challenges. One major challenge is the availability of a proper metric to evaluate individual fairness, especially for probabilistic classifiers. In this study, we propose a framework PCIndFair to assess the individual fairness of probabilistic classifiers. Unlike current individual fairness measures, our framework considers probability distribution rather than the final classification outcome, which is suitable for capturing the dynamic …
Dynamic Target Assignment Of Multiple Unmanned Aerial Vehicles Based On Clustering Of Network Nodes, Tuo Zhao, Hanqiang Deng, Jialong Gao, Jian Huang
Dynamic Target Assignment Of Multiple Unmanned Aerial Vehicles Based On Clustering Of Network Nodes, Tuo Zhao, Hanqiang Deng, Jialong Gao, Jian Huang
Journal of System Simulation
Abstract: In order to solve the problem that the distributed multi-UAV target assignment algorithm is prone to communication redundancy, which leads to the large communication scale of formation, a multi-UAV dynamic target assignment algorithm (CU-CBBA) based on node clustering in communication network is proposed.The algorithm introduces the communication network node grouping clustering strategy. According to the node's degree centrality, feature vector centrality, intermediate centrality and other attributes, the network node importance ranking model is established. A group of key nodes in the network topology structure are selected and the network topology node clustering is completed according to the shortest …
Research On Modeling And Scheduling Of Virtual Power Plant With Dual Demand Response, Qiang Chen, Yi Wang, Kangshun Li
Research On Modeling And Scheduling Of Virtual Power Plant With Dual Demand Response, Qiang Chen, Yi Wang, Kangshun Li
Journal of System Simulation
Abstract: Virtual power plant technology provides an effective means to aggregate distributed power and user side resources to participate in power scheduling. Most of the existing research focus on the scheduling optimization of distributed energy instead of the demand response of user side. The user side resources are divided into contracted reliable response load and non-contracted random response load, and the load response is regulated through price adjustment mechanism to adapt to the change of distributed. A virtual power plant optimal scheduling model with dual demands response is constructed, in which the maximizing overall profit of the power grid is …
Voltage And Reactive Power Combinational Evaluation Of Regional Power Grid Based On Ewm-Ahp-Bp Neural Network, Yuqi Ji, Huan Xie, Shaoyu Shi, Ping He, Nan Jin, Huili Wang
Voltage And Reactive Power Combinational Evaluation Of Regional Power Grid Based On Ewm-Ahp-Bp Neural Network, Yuqi Ji, Huan Xie, Shaoyu Shi, Ping He, Nan Jin, Huili Wang
Journal of System Simulation
Abstract: In order to quantitatively evaluate the influence of renewable energy access on voltage and reactive power operation, a combinational evaluation method of voltage and reactive power based on EWM-AHP-BP neural network is proposed to carry out the multi-objective evaluation weight calculation. Considering voltage qualified rate, voltage fluctuation, power factor qualified rate and reactive power reserve, the comprehensive evaluation model is established. The operation data of renewable energy and power load are clustered to divide the typical scenarios and the evaluation model under multiple scenarios is scored by the combination method of entropy weight method and analytic hierarchy process. The …
Research On Modeling And Solution Method Of Operational Tasks Assignment, Yue Ma, Lin Wu, Shengming Guo
Research On Modeling And Solution Method Of Operational Tasks Assignment, Yue Ma, Lin Wu, Shengming Guo
Journal of System Simulation
Abstract: Aiming at the prewar operational tasks assignment in operation task planning, a multi constraint model of operational tasks assignment is constructed to describe the dynamic mapping relationship between operational tasks and operational units. The solution strategy of decision space pruning and constraint condition judgment is proposed, and the methods of decision variable coding, assignment scheme decoding and phased fitness calculation are described. Differential evolution algorithm is used to work out the solution. The experimental results show that the multi constraint assignment model and solution algorithm can effectively reduce the scale of decision space, and can improve the rationality …
Knowledge Graph-Based Process Knowledge Reasoning Method For Intelligent Production System, Weikai Yang, Yan Wang, Zhicheng Ji
Knowledge Graph-Based Process Knowledge Reasoning Method For Intelligent Production System, Weikai Yang, Yan Wang, Zhicheng Ji
Journal of System Simulation
Abstract: Aiming at the disadvantages of high redundancy and weakness between knowledge and data in intelligent production system, and the difficulty to perform knowledge reasoning, a process knowledge reasoning method for knowledge maps is proposed. The input information is semantically labeled and classified, the characteristics of the information match are extracted, the extracted local feature and global feature are associated through graph convolution method, and the feature of the difference value information is integrated and mapped with the constructed knowledge graph. Different reasoning rules are used according to different reasoning types, and the association and topology information between instances are …
Dual Resource Constrained Flexible Job Shop Energy-Saving Scheduling Considering Delivery Time, Hongliang Zhang, Jingru Xu, Bo Tan, Gongjie Xu
Dual Resource Constrained Flexible Job Shop Energy-Saving Scheduling Considering Delivery Time, Hongliang Zhang, Jingru Xu, Bo Tan, Gongjie Xu
Journal of System Simulation
Abstract: To handle the flexible job shop energy-saving scheduling with machines and workers constraints, on the considering of delivery time, the optimization model of dual resource constrained flexible job shop energy-saving scheduling is established with the goal of minimizing the total earliness and tardiness penalties, and total energy consumption. An improved non-dominated sorting genetic algorithm II(INSGA-II) is proposed. Aiming at the optimized objectives, a three-stage decoding method is designed to gain more feasible solutions. The dynamic adaptive crossover and mutation operators are applied to get more excellent individuals. The crowding distance is improved to obtain a population with better …
Research On Improvement Of Social Force Model Based On Non-Motor Vehicle Active Overtaking Behavior, Minghui Yang, Rui Zhang, Qiaobing Yan, Jiahe Wang
Research On Improvement Of Social Force Model Based On Non-Motor Vehicle Active Overtaking Behavior, Minghui Yang, Rui Zhang, Qiaobing Yan, Jiahe Wang
Journal of System Simulation
Abstract: Aiming at the social force model not to illustrate the active overtaking behavior of the rear non-motor vehicle to the front vehicle, an improved social force model is proposed. The traffic behavior characteristics of non-motorized vehicles mixed flow during the active overtaking is analyzed. Considering the compressible characteristics of non-motorized vehicle distancing in different density environments, the model is improved by presenting the concept of dynamic perception space and introducing the overtaking force into the social force model. The model is verified by analyzing the active overtaking behavior, active overtaking distance and speed-density basic graphs. The results indicate that …
Research On Workshop Logic Modeling And Simulation Based On Finite State Machine, Mingyuan Liu, Jiaxiang Xie, Hao Wu, Jianlin Fu, Guofu Ding
Research On Workshop Logic Modeling And Simulation Based On Finite State Machine, Mingyuan Liu, Jiaxiang Xie, Hao Wu, Jianlin Fu, Guofu Ding
Journal of System Simulation
Abstract: Discrete manufacturing is common in aircraft, ships, electronic equipment, automobile and other manufacturing industries. To ensure the correctness and flexibility of the modeling and simulation process of discrete manufacturing workshops, a logical modeling and simulation method for the production process of discrete manufacturing workshop is proposed. Based on the theory of discrete event dynamic systems and finite-state machines, the attributes and behaviors of the key elements of the discrete manufacturing workshop are abstracted into a unified logic model, and the function of various elements are realized through inheritance. A production process simulation algorithm is designed for the unified model …
Dynamics Modeling And Online Prediction Of Energy Consumption Of Discrete Manufacturing System, Wei Chen, Yan Wang, Zhicheng Ji
Dynamics Modeling And Online Prediction Of Energy Consumption Of Discrete Manufacturing System, Wei Chen, Yan Wang, Zhicheng Ji
Journal of System Simulation
Abstract: Aiming at the traditional energy consumption modeling methods of discrete manufacturing system being difficult to adapt to the complexity and variability of working conditions, an online dynamic energy consumption modeling method based on real-time data is proposed. The energy consumption affecting factors are determined by analyzing the operation mechanism of the discrete manufacturing system and equipment. An online sequential extreme learning machine algorithm that can dynamically adjust the number of hidden layer nodes is proposed to construct the energy consumption model. The real-time data can update the model quickly. Bernstein's inequality is introduced to improve the model data screening …
Research Progress Of Opponent Modeling Based On Deep Reinforcement Learning, Haotian Xu, Long Qin, Junjie Zeng, Yue Hu, Qi Zhang
Research Progress Of Opponent Modeling Based On Deep Reinforcement Learning, Haotian Xu, Long Qin, Junjie Zeng, Yue Hu, Qi Zhang
Journal of System Simulation
Abstract: Deep reinforcement learning is an agent modeling method with both deep learning feature extraction ability and reinforcement learning sequence decision-making ability, which can make up for the depleted non-stationary adaptation, complex feature selection and insufficient state-space representation ability of traditional opponent modeling. The deep reinforcement learning-based opponent modeling methods are divided into two categories, explicit modeling and implicit modeling, and the corresponding theories, models, algorithms and applicable scenarios are sorted out according to the categories. The applications of deep reinforcement learning-based opponent modeling techniques on different fields are introduced. The key problems and future development are summarized to provide …
Adaptive Correction Tracking Algorithm Based On Detector And Locator Fusion, Yecai Guo, Cheng Liu
Adaptive Correction Tracking Algorithm Based On Detector And Locator Fusion, Yecai Guo, Cheng Liu
Journal of System Simulation
Abstract: In order to avoid tracking failure caused by occlusion, rotation and other factors in complex dynamic scenes, an adaptive correction tracking algorithm based on detector and locator fusion is proposed. The locator trains a convolutional neural network (CNN) filter for location estimation by extracting the deep features of target. The CNN filter adds two layers of shallow features to the three layers of the convolution features of original CF2 algorithm, which enhances the extraction of target texture information. The detector calculates the confidence score by extracting histogram of oriented gradient(HOG) feature of target and combining the context information. …