Open Access. Powered by Scholars. Published by Universities.®
Artificial Intelligence and Robotics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Engineering (1598)
- Computer Engineering (1536)
- Numerical Analysis and Scientific Computing (1505)
- Operations Research, Systems Engineering and Industrial Engineering (1500)
- Systems Science (1490)
-
- Social and Behavioral Sciences (55)
- Databases and Information Systems (45)
- Theory and Algorithms (38)
- Electrical and Computer Engineering (31)
- Data Science (29)
- Graphics and Human Computer Interfaces (24)
- Information Security (24)
- Software Engineering (24)
- Other Computer Sciences (22)
- Law (18)
- Medicine and Health Sciences (18)
- Arts and Humanities (15)
- Business (14)
- Public Affairs, Public Policy and Public Administration (14)
- Statistics and Probability (14)
- Life Sciences (13)
- Applied Mathematics (12)
- Mathematics (12)
- Robotics (12)
- Civil and Environmental Engineering (10)
- Communication (10)
- Science and Technology Law (10)
- Institution
-
- China Simulation Federation (1490)
- Singapore Management University (86)
- San Jose State University (35)
- University of Malaya (22)
- Old Dominion University (19)
-
- Technological University Dublin (15)
- Chulalongkorn University (11)
- California Polytechnic State University, San Luis Obispo (9)
- Missouri University of Science and Technology (9)
- University of Kentucky (9)
- University of Arkansas, Fayetteville (8)
- University of Denver (8)
- University of Texas at El Paso (8)
- Air Force Institute of Technology (7)
- City University of New York (CUNY) (6)
- University of Nevada, Las Vegas (6)
- University of South Florida (6)
- MBZUAI (5)
- New Jersey Institute of Technology (5)
- University of Nebraska - Lincoln (5)
- West Virginia University (5)
- Boise State University (4)
- Edith Cowan University (4)
- Southern Methodist University (4)
- The University of Southern Mississippi (4)
- Walden University (4)
- Wayne State University (4)
- Embry-Riddle Aeronautical University (3)
- Fordham University (3)
- James Madison University (3)
- Keyword
-
- Simulation (76)
- Machine learning (66)
- Artificial intelligence (42)
- Deep learning (36)
- Machine Learning (28)
-
- Artificial Intelligence (24)
- Numerical simulation (20)
- Particle swarm optimization (20)
- Virtual reality (19)
- Genetic algorithm (18)
- Modeling (18)
- Deep Learning (17)
- Neural network (16)
- Modeling and simulation (14)
- Neural networks (13)
- Optimization (13)
- Visualization (13)
- Fault diagnosis (12)
- Reinforcement learning (12)
- System simulation (12)
- AI (11)
- Multi-objective optimization (11)
- Simulation model (11)
- Complex network (10)
- Computer vision (10)
- Feature extraction (10)
- Robustness (10)
- Scheduling (10)
- Virtual simulation (10)
- Parameter identification (9)
- Publication
-
- Journal of System Simulation (1490)
- Research Collection School Of Computing and Information Systems (73)
- Master's Projects (34)
- Student Works (2020-2029) (22)
- Chulalongkorn University Theses and Dissertations (Chula ETD) (11)
-
- Conference papers (8)
- Dissertations (8)
- Electronic Theses and Dissertations (8)
- Master's Theses (8)
- Theses and Dissertations (8)
- Open Access Theses & Dissertations (7)
- Articles (6)
- Doctoral Dissertations (6)
- Faculty Publications (6)
- USF Tampa Graduate Theses and Dissertations (6)
- Graduate Theses, Dissertations, and Problem Reports (ETD) (5)
- Computer Science and Computer Engineering Undergraduate Honors Theses (4)
- Theses (4)
- Theses and Dissertations--Computer Science (4)
- Walden Dissertations and Doctoral Studies (4)
- Cybersecurity Undergraduate Research Showcase (3)
- Dissertations and Theses Collection (Open Access) (3)
- Dissertations, Theses, and Capstone Projects (3)
- Faculty Works (3)
- Machine Learning Faculty Publications (3)
- Masters Theses (3)
- Minnesota Journal of Law, Science & Technology (3)
- Publications (3)
- Research outputs 2014 to 2021 (3)
- Senior Independent Study Theses (3)
- Publication Type
Articles 61 - 90 of 1914
Full-Text Articles in Artificial Intelligence and Robotics
A Study Of Multi-Task And Region-Wise Deep Learning For Food Ingredient Recognition, Jingjing Chen, Bin Zhu, Chong-Wah Ngo, Tat-Seng Chua, Yu-Gang Jiang
A Study Of Multi-Task And Region-Wise Deep Learning For Food Ingredient Recognition, Jingjing Chen, Bin Zhu, Chong-Wah Ngo, Tat-Seng Chua, Yu-Gang Jiang
Research Collection School Of Computing and Information Systems
Food recognition has captured numerous research attention for its importance for health-related applications. The existing approaches mostly focus on the categorization of food according to dish names, while ignoring the underlying ingredient composition. In reality, two dishes with the same name do not necessarily share the exact list of ingredients. Therefore, the dishes under the same food category are not mandatorily equal in nutrition content. Nevertheless, due to limited datasets available with ingredient labels, the problem of ingredient recognition is often overlooked. Furthermore, as the number of ingredients is expected to be much less than the number of food categories, …
Nearest Centroid: A Bridge Between Statistics And Machine Learning, Manoj Thulasidas
Nearest Centroid: A Bridge Between Statistics And Machine Learning, Manoj Thulasidas
Research Collection School Of Computing and Information Systems
In order to guide our students of machine learning in their statistical thinking, we need conceptually simple and mathematically defensible algorithms. In this paper, we present the Nearest Centroid algorithm (NC) algorithm as a pedagogical tool, combining the key concepts behind two foundational algorithms: K-Means clustering and K Nearest Neighbors (k- NN). In NC, we use the centroid (as defined in the K-Means algorithm) of the observations belonging to each class in our training data set and its distance from a new observation (similar to k-NN) for class prediction. Using this obvious extension, we will illustrate how the concepts of …
Interventional Few-Shot Learning, Zhongqi Yue, Zhang Hanwang, Qianru Sun, Xian-Sheng Hua
Interventional Few-Shot Learning, Zhongqi Yue, Zhang Hanwang, Qianru Sun, Xian-Sheng Hua
Research Collection School Of Computing and Information Systems
We uncover an ever-overlooked deficiency in the prevailing Few-Shot Learning (FSL) methods: the pre-trained knowledge is indeed a confounder that limits the performance. This finding is rooted from our causal assumption: a Structural Causal Model (SCM) for the causalities among the pre-trained knowledge, sample features, and labels. Thanks to it, we propose a novel FSL paradigm: Interventional Few-Shot Learning (IFSL). Specifically, we develop three effective IFSL algorithmic implementations based on the backdoor adjustment, which is essentially a causal intervention towards the SCM of many-shot learning: the upper-bound of FSL in a causal view. It is worth noting that the contribution …
Causal Intervention For Weakly-Supervised Semantic Segmentation, Zhang Dong, Hanwang Zhang, Jinhui Tang, Xian-Sheng Hua, Qianru Sun
Causal Intervention For Weakly-Supervised Semantic Segmentation, Zhang Dong, Hanwang Zhang, Jinhui Tang, Xian-Sheng Hua, Qianru Sun
Research Collection School Of Computing and Information Systems
We present a causal inference framework to improve Weakly-Supervised Semantic Segmentation (WSSS). Specifically, we aim to generate better pixel-level pseudo-masks by using only image-level labels --- the most crucial step in WSSS. We attribute the cause of the ambiguous boundaries of pseudo-masks to the confounding context, e.g., the correct image-level classification of "horse'' and "person'' may be not only due to the recognition of each instance, but also their co-occurrence context, making the model inspection (e.g., CAM) hard to distinguish between the boundaries. Inspired by this, we propose a structural causal model to analyze the causalities among images, contexts, and …
Goamlp: Network Intrusion Detection With Multilayer Perceptron And Grasshopper Optimization Algorithm, Farshid Bagheri Saravi
Goamlp: Network Intrusion Detection With Multilayer Perceptron And Grasshopper Optimization Algorithm, Farshid Bagheri Saravi
Student Scholarship
In this paper, an intrusion detection system is introduced that uses data mining and machine learning concepts to detect network intrusion patterns. In the proposed method, an artificial neural network (ANN) is used as a learning technique in intrusion detection. The metaheuristic algorithm with the swarm-based approach is used to reduce intrusion detection errors. In the proposed method, the Grasshopper Optimization Algorithm (GOA) is used for better and more accurate learning of ANNs to reduce intrusion detection error rate. The role of the GOAMLP algorithm is to minimize the intrusion detection error in the neural network by selecting useful parameters …
Computational Cognition And Deep Learning, Andy Malinsky
Computational Cognition And Deep Learning, Andy Malinsky
The Compass
No abstract provided.
Energy-Based Neural Modelling For Large-Scale Multiple Domain Dialogue State Tracking, Anh Duong Trinh, Robert J. Ross, John D. Kelleher
Energy-Based Neural Modelling For Large-Scale Multiple Domain Dialogue State Tracking, Anh Duong Trinh, Robert J. Ross, John D. Kelleher
Conference papers
Scaling up dialogue state tracking to multiple domains is challenging due to the growth in the number of variables being tracked. Furthermore, dialog state tracking models do not yet explicitly make use of relationships between dialogue variables, such as slots across domains. We propose using energy-based structure prediction methods for large-scale dialogue state tracking task in two multiple domain dialogue datasets. Our results indicate that: (i) modelling variable dependencies yields better results; and (ii) the structured prediction output aligns with the dialogue slot-value constraint principles. This leads to promising directions to improve state-of-the-art models by incorporating variable dependencies into their …
Autonomous Vehicles And The Ethical Tension Between Occupant And Non-Occupant Safety, Jason Borenstein, Joseph Herkert, Keith Miller
Autonomous Vehicles And The Ethical Tension Between Occupant And Non-Occupant Safety, Jason Borenstein, Joseph Herkert, Keith Miller
The Journal of Sociotechnical Critique
Given that the creation and deployment of autonomous vehicles is likely to continue, it is important to explore the ethical responsibilities of designers, manufacturers, operators, and regulators of the technology. We specifically focus on the ethical responsibilities surrounding autonomous vehicles that these stakeholders have to protect the safety of non-occupants, meaning individuals who are around the vehicles while they are operating. The term “non-occupants” includes, but is not limited to, pedestrians and cyclists. We are particularly interested in how to assign moral responsibility for the safety of non-occupants when autonomous vehicles are deployed in a complex, land-based transportation system.
Machine Learning Augmentation Micro-Sensors For Smart Device Applications, Mohammad H. Hasan
Machine Learning Augmentation Micro-Sensors For Smart Device Applications, Mohammad H. Hasan
Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research
Novel smart technologies such as wearable devices and unconventional robotics have been enabled by advancements in semiconductor technologies, which have miniaturized the sizes of transistors and sensors. These technologies promise great improvements to public health. However, current computational paradigms are ill-suited for use in novel smart technologies as they fail to meet their strict power and size requirements. In this dissertation, we present two bio-inspired colocalized sensing-and-computing schemes performed at the sensor level: continuous-time recurrent neural networks (CTRNNs) and reservoir computers (RCs). These schemes arise from the nonlinear dynamics of micro-electro-mechanical systems (MEMS), which facilitates computing, and the inherent ability …
New Methods For Deep Learning Based Real-Valued Inter-Residue Distance Prediction, Jacob Barger
New Methods For Deep Learning Based Real-Valued Inter-Residue Distance Prediction, Jacob Barger
Theses
Background: Much of the recent success in protein structure prediction has been a result of accurate protein contact prediction--a binary classification problem. Dozens of methods, built from various types of machine learning and deep learning algorithms, have been published over the last two decades for predicting contacts. Recently, many groups, including Google DeepMind, have demonstrated that reformulating the problem as a multi-class classification problem is a more promising direction to pursue. As an alternative approach, we recently proposed real-valued distance predictions, formulating the problem as a regression problem. The nuances of protein 3D structures make this formulation appropriate, allowing predictions …
Under Impact Of Non-Motor Vehicle Violation An Analysis On Vehicle Operation Efficiency, Sun Di, Zhou Jin, Sijia Liu, Xiaoming Zhang, Xueying Gao
Under Impact Of Non-Motor Vehicle Violation An Analysis On Vehicle Operation Efficiency, Sun Di, Zhou Jin, Sijia Liu, Xiaoming Zhang, Xueying Gao
Journal of System Simulation
Abstract: In order to study the impact of non-motor vehicle violations on motor vehicle traffic efficiency at signalized intersections, the non-motor vehicle traffic behaviors are analyzed. An actual intersection is selected as study object, the main violation behaviors of on selected intersection are analyzed by using the linear regression model. For traffic light violation behavior of non-motor vehicles, the violation rate is modeled by using logistic model, and the results are analyzed. At the signal controlled intersection, non-motor vehicle violations affect the normal motor vehicles, and time is delayed. The delay time of motor vehicle under non-motor vehicle …
Time-Varying Parameter System Modeling Method Based On Zonotope-Ellipsoid Double Filtering, Ziyun Wang, Peiyu Wang, Yacong Zhan
Time-Varying Parameter System Modeling Method Based On Zonotope-Ellipsoid Double Filtering, Ziyun Wang, Peiyu Wang, Yacong Zhan
Journal of System Simulation
Abstract: The traditional system modeling method using zonotopes as the feasible parameter sets islikely to increase the computational complexity of the algorithm due to the increasing dimensions of the zonotope shape matrix. This paper proposes a time-varying parameter modeling systems method based on zonotope-ellipsoid double filtering technique. Considering the time-varying parameters, a zonotope with the minimum volume is obtained during the iterations of the intersection with the constraint strip. After transforming the shape matrix of the zonotope, the dimensionality reduction is performed, instead of directly finding the row sum of the extended shape matrix, to reduce the algorithm conservativeness originated …
Research On Configurable Simulation Integration Technology For Equipment Software, Yuanyuan Wang, Yuxin Duan, Guangzhao Song
Research On Configurable Simulation Integration Technology For Equipment Software, Yuanyuan Wang, Yuxin Duan, Guangzhao Song
Journal of System Simulation
Abstract: The problems of the traditional distributed digital simulation system are analyzed. The method of constructing the digital simulation system based on the equipment software is studied. The configurable simulation integration middleware is designed. The overall structure of the configurable middleware is designed and the design ideas of each module are briefly summarized. An example of a digital simulation system with networked transformation of equipment shows that the middleware can be effectively and flexibly configured and can provide support for constructing digital simulation system with software, which can be promoted and used in other simulation systems.
Research On Multi-Objective Optimization Method Based On Model, Jianjun Liu, Guangya Si, Yanzheng Wang, Dachuan He
Research On Multi-Objective Optimization Method Based On Model, Jianjun Liu, Guangya Si, Yanzheng Wang, Dachuan He
Journal of System Simulation
Abstract: There is a model-based algorithm for the optimization of multiple objective functions by means of black-box evaluation is proposed. The algorithm iteratively generates candidate solutions from a mixture distribution over the solution space and updates the mixture distribution based on the sampled solutions’ domination count, such that the future search is biased towards the set of Pareto optimal solutions. The proposed algorithm seeks to find a mixture distribution on the solution space so that each component of the mixture distribution is a degenerate distribution centered at a Pareto optimal solution and each estimated Pareto optimal solution is uniformly spread …
Research And Application Of A Lightweight Real-Time Human Posture Detection Model, Hongkun Zhu, Jiawei Yin, Wenyu Feng, Hua Liang, Minrui Fei, Kun Zhang
Research And Application Of A Lightweight Real-Time Human Posture Detection Model, Hongkun Zhu, Jiawei Yin, Wenyu Feng, Hua Liang, Minrui Fei, Kun Zhang
Journal of System Simulation
Abstract: The traditional OpenPose model has good accuracy but slow speed in human posture detection. In order to accelerate the detection speed and reduce the model on condition of the detection precision, based on the traditional OpenPose model, the residual network with second-order term fusion is used to extract the low-level features, the weights of the trained model are pruned by the L1 norm weight, and an improved OpenPose model is proposed. Experiments show that when the detection accuracy is approximately equal to original model, the model size reduces to about 8%, the parameters reduces by nearly 83%, and the …
Construction And Test Method Of A Semi-Physical Simulation System For Laser Driving Guidance Weapon, Zhang Xiang, Mengyan Liu, Zhang Peng, Kewei Zhu, Xiaodong Yan
Construction And Test Method Of A Semi-Physical Simulation System For Laser Driving Guidance Weapon, Zhang Xiang, Mengyan Liu, Zhang Peng, Kewei Zhu, Xiaodong Yan
Journal of System Simulation
Abstract: To achieve the previous semi-physical simulation of the laser beam-guided weapon, the two-dimensional translation system must be used. But the technical index of the two-dimensional translation system is not high enough to meet the requirements of the relative motion simulation speed and acceleration of the projectile. To solve the problem, a new method and test method for the semi-physical simulation system of laser driving guidance weapon is proposed. The “two-axis turret + load bracket” simulation system construction method is adopted to replace the linear motion of the two-dimensional translation system by the rotational angular motion of the …
Two Gd Atoms Adsorbed On Zigzag Graphene Nanoribbon:A First-Principles Study, Weifeng Xie, Zuo Xu
Two Gd Atoms Adsorbed On Zigzag Graphene Nanoribbon:A First-Principles Study, Weifeng Xie, Zuo Xu
Journal of System Simulation
Abstract: A giant Rashba-type spin splitting is highly critical for the application of spintronics, but one-dimensional magnetic systems are rarely involved. In order to explore the characteristics and strength of Rashba effect in one-dimensional magnetic systems, two Gd atoms adsorbed on Zigzag graphene nanoribbon system is proposed. The characteristics and strength of the Rashba effect in different magnetization directions and the magnetic anisotropy of the system are analyzed through the first-principles calculations. The results show that the antiferromagnetic ground state system has strong Rashba strength and out-of-plane magnetic anisotropy. In addition, the Rashba effect in magnetic system needs to …
Generalized Zero-Inflated Binomial Distribution Model Aimed At Air Quality Data Analysis, Benyue Su, Pengpeng Xu, Sheng Min
Generalized Zero-Inflated Binomial Distribution Model Aimed At Air Quality Data Analysis, Benyue Su, Pengpeng Xu, Sheng Min
Journal of System Simulation
Abstract: For the problem of the quality monitoring and counting of excessive gas emissions in chemical industry parks, a generalized zero-inflated binomial distribution model is constructed. Statistics show that the times of number of excessive gas emissions has a typical zero-inflated feature. The traditional zero-inflated Poisson model and negative binomial regression model and so on will underestimate the probability of zero inflation. A generalized zero-inflated binomial distribution model is constructed by extending the traditional binomial regression model to a more general form. This model satisfies the characteristic that the expectation is less than the variance, and better solves the problems …
Hyper-Heuristic De Algorithm For Solving Zero-Wait Fermentation Process Schedulinge, Shen Peng, Wang Yan, Zhicheng Ji, Jianhua Zhang
Hyper-Heuristic De Algorithm For Solving Zero-Wait Fermentation Process Schedulinge, Shen Peng, Wang Yan, Zhicheng Ji, Jianhua Zhang
Journal of System Simulation
Abstract: A class of zero-wait fermentation process scheduling issues with batch process characteristics are researched. In order to solve the problem of easy deterioration in the process, a super heuristic difference algorithm is proposed, and the maximum makespan is minimized as the optimization goal. The algorithm is divided into two layers. The upper layer is an improved adaptive differential evolution algorithm to select and sort the heuristic operations in lower layer. The lower layer is combined and sorted into a new algorithm to operate on the problem domain, adding simulated annealing algorithm to avoid falling into local optimization. The method …
Modeling And Relevance Analysis Of Urban Epidemic Transmission And Work Resumption Intensity, Gan Mi, Yunyi Tian, Wenchang Zhang, Xihan Zhao
Modeling And Relevance Analysis Of Urban Epidemic Transmission And Work Resumption Intensity, Gan Mi, Yunyi Tian, Wenchang Zhang, Xihan Zhao
Journal of System Simulation
Abstract: On the basis of multi-source big data, the model for analyzing the population migration changes and manpower gaps caused by the COVID-19 epidemic in 34 typical cities across the country is constructed , and the work resumption intensity of other cities is predicited by using the migration base constructed. The SEIR model is used to estimate the basic reproduction number in each city since the simulate results show that it can emulate the transmission trend of this epidemic accurately, and the retrospective matrix analysis of the work resumption intensity is combined with the manpower gap to summarize the anti-epidemic …
Research On Dynamic Flexible Job Shop Scheduling Problem Based On Dynamic Interaction Layer, Zhang Xiang, Wang Yan, Zhicheng Ji
Research On Dynamic Flexible Job Shop Scheduling Problem Based On Dynamic Interaction Layer, Zhang Xiang, Wang Yan, Zhicheng Ji
Journal of System Simulation
Abstract: In order to quickly response to the unforeseen circumstances in flexible job shop, a dynamic flexible job shop scheduling model is constructed, which takes the overall production time and the completion time of emergency orders as the optimization objectives. For the model, a dynamic interaction layer (DIL) model, which has a better performance on DFJSP, is proposed to replace the scroll window. Particle swarm genetic hybrid algorithm (PSGA) is designed to combine the particle swarm optimization algorithm with the genetic algorithm to enhance the ability of local search. Aiming at the unexpected urgent orders in flexible job shop, …
Echo Simulation And Verification Of High Resolution Range Profile, Xiaolin Li, Cheng Yu, Haifei Zang, Shuge Wang, Liu Li, Qingqing Yuan
Echo Simulation And Verification Of High Resolution Range Profile, Xiaolin Li, Cheng Yu, Haifei Zang, Shuge Wang, Liu Li, Qingqing Yuan
Journal of System Simulation
Abstract: In order to realize the echo simulation and verification of high-resolution range profile in laboratory environment, the multi-scattering point model and wideband LFM echo signal model are given, and the time-domain convolution and high-precision delay realization methods in echo simulation process are described. According to the different signal bandwidth forms of the tested equipments, a wideband echo simulator is used to realize the corresponding high-resolution range image echo. By comparing with the digital simulation results of the target characteristic modeling software, the fidelity of the high-resolution range echo simulation is verified. Simulation verification is carried out with an aircraft …
Multi-Agent Simulation Model For Covid-19 Virus Prevention And Control, Lihu Pan, Shipeng Qin, Xiaowen Li, Feiping Lu, Fenyu Yang
Multi-Agent Simulation Model For Covid-19 Virus Prevention And Control, Lihu Pan, Shipeng Qin, Xiaowen Li, Feiping Lu, Fenyu Yang
Journal of System Simulation
Abstract: The prevention and control of the novel coronavirus (COVID-19) is the priority work to maintain the public health security of the world nowadays. The COVID-19 prevention and control model using multi-agent modeling and simulation technology is proposed. The model can simulate the different dynamic development trend of the epidemic under different prevention and control measures. Taking Taiyuan as an example, according to the researched COVID-19 transmission rules, the prevention and control simulation of COVID-19 has been achieved under the designing rule of the interactive infection process and status transition process between various resident agents. Multi-scenario simulation experiments are realized …
Design And Implementation Of Cloth Virtual Simulation System For Group Performance, Xiaotian Sun, Boxiang Xiao, Zhengdong Liu
Design And Implementation Of Cloth Virtual Simulation System For Group Performance, Xiaotian Sun, Boxiang Xiao, Zhengdong Liu
Journal of System Simulation
Abstract: Clothing plays an important role in group performance activities and affects directly the overall performance effect. In order to achieve the goal of virtual design and virtual exercise of group performance costume, a virtual simulation system is designed and implemented. The human body model is established by CLO3D, and then individual clothing model is constructed. After the human body and clothing model are imported into Unity, the clothing material is adjusted and the texture map is added. The group model is generated by copying individual clothing models of human body and clothing in Unity. The interactive interface of virtual …
Optimal Scheduling And Decision Making Method For Dynamic Flexible Job Shop, Wang Yan, Ding Yu
Optimal Scheduling And Decision Making Method For Dynamic Flexible Job Shop, Wang Yan, Ding Yu
Journal of System Simulation
Abstract: For multi-objective dynamic flexible job-shop scheduling, an improved multi-objective differential evolution algorithm is proposed. The adaptive cross-mutation operator is introduced into the differential evolution algorithm to improve its global search capability. The fast non-dominated sorting method based on immunological principles is introduced to improve the quality of the solution set in the selection and sorting. An improved TOPSIS-G1-EVM comprehensive decision-making method is proposed. The comprehensive weight of G1-EVM is calculated by Nash equilibrium theory. The comprehensive weight and TOPSIS evaluation system are combined to evaluate each dispatching scheme. The experimental results show that the optimal scheduling algorithm is superior …
Fast 3d Medical Image Registration Based On Geometric Feature Invariants, Juping Gu, Tianyu Cheng, Jianping Wang, Hua Liang, Fengshen Zhao, Jiang Ling
Fast 3d Medical Image Registration Based On Geometric Feature Invariants, Juping Gu, Tianyu Cheng, Jianping Wang, Hua Liang, Fengshen Zhao, Jiang Ling
Journal of System Simulation
Abstract: Aiming at the of large amount of computational data and low registration efficiency in 3D cranial medical image registration, a fast registration method based on geometric feature space constraints is proposed. The algorithm extracts three-dimensional contour point clusters, and proposes a feature construction method based on the optimal fitting ring of point clusters. The feature rings and the centroids of each layer are used as feature quantities, and the fast registration is completed by using Iterative Closest Point (ICP) method. The experimental results show that the method has less computation amount, high satisfactory registration accuracy and much faster registration …
Research On Improvement Of Parameters Calibration Method Of Microscopic Traffic Simulation Model, Chenjing Zhou, Yacong Gao, Rong Jian
Research On Improvement Of Parameters Calibration Method Of Microscopic Traffic Simulation Model, Chenjing Zhou, Yacong Gao, Rong Jian
Journal of System Simulation
Abstract: Model parameter calibration is the precondition of application of micro traffic simulation technology. In view of the lack of refined analysis in the model parameter calibration classification and calibration result determination, the corresponding improvement is proposed. The parameter calibration system divides global parameters and local parameters, provides a micro-simulation model parameter calibration method that combines engineering measurement and intelligent optimization. Based on the information entropy as the analysis index of the parameter calibration results, a method of parameter recursion after clustering is proposed. On the basis of the actual survey data of signalized intersections, A simulation experiments and …
Design And Simulation On A Novel Sliding Mode Control For Linear Induction Motor, Kaiwei Han, Wang Yan, Zhicheng Ji
Design And Simulation On A Novel Sliding Mode Control For Linear Induction Motor, Kaiwei Han, Wang Yan, Zhicheng Ji
Journal of System Simulation
Abstract: The speed-tracking problem of linear induction motors under the influence of unmatched disturbances is studied. Based on the extended disturbance observers, the novel sliding mode controllers are designed to make the motor have effective response characteristics under unmatched disturbances. The extended disturbance observersis designed for the unmatched disturbances in the linear induction motor model with edge effects. The observations of the disturbance derivatives are filtered. The novel sliding mode controllers are designed based on the observations of the disturbances and their derivatives. The simulations results show that the designed controller has effective response characteristics and robustness. In addition, it …
A Fast Latin Hyper Cube Experiment Design Method Based On Soduku Grouping, Tiantian Zhang, Li Ni, Guanghong Gong, Yuanjie Lu
A Fast Latin Hyper Cube Experiment Design Method Based On Soduku Grouping, Tiantian Zhang, Li Ni, Guanghong Gong, Yuanjie Lu
Journal of System Simulation
Abstract: In order to solve the long optimization time and parameter level combination explosion in the complex experiment design space of Latin Hypercube design, which is one of the most popular method in experiment design, a fast Soduku grouping-based method is proposed. The optimal seed design is expanded and transformed in the grouped spaces. Experiments are conducted to compare the Soduku grouping-based Latin Hypercube design method with other two commonly used Latin Hypercube design methods in the middle and high dimension experiment space. The results show that Soduku grouping method is more efficient in computation and has better space-filling performance.
Container-Based Automatic Packaging Technology For Complex System Simulation Application, Wang Shuai, Zhu Feng, Yiping Yao, Wenjie Tang, Yuhao Xiao
Container-Based Automatic Packaging Technology For Complex System Simulation Application, Wang Shuai, Zhu Feng, Yiping Yao, Wenjie Tang, Yuhao Xiao
Journal of System Simulation
Abstract: Container-based technology provides a new solution for the rapid and flexible deployment of complex system simulation applications. Container supports service-based packaging of simulation applications, which greatly reduces the difficulty of deploying simulation applications. Current packaging technology mainly relies on manually writing Dockerfile, which results in low packaging efficiency and human errors. A container-based automatic packaging technology for complex system simulation application is proposed, and the reusable library component template is defined. Combined image template is generated by combining simulation application and library component templates. Dockerfile is generated by the combined template after syntax optimization and error detection. The experiments …