Computer Sciences Commons^™

Joint Optimization Strategy Of Computing Offloading And Edge Caching For Intelligent Connected Vehicles, Fei Ding, Yuchen Sha, Ying Hong, Xiao Kuai, Dengyin Zhang

Journal of System Simulation

To guarantee the low-delay communication of intelligent connected vehicles, the V2X channel model and the multi-access edge computing (MEC) technology, are used to carry out the research of the joint optimization strategy of computing offloading and edge caching.An intelligent connected vehicle with task offloading and edge caching model least-deep deterministic policy gradient(L-DDPG) is developed.By integrating the vehicular local and edge computing resources, the classification processing of different computing tasks in V2X scenarios is supported.The vehicular computing request is prejudged by edge platform to ensure the rapid response of continuous homogeneous computing tasks. Combining with the least recently …

Multi-Robot Formation Control Based On Improved Virtual Spring Model, Yimei Chen, Xiaofan Shi, Baoquan Li

Journal of System Simulation

Aiming at multi-robot system being difficult to avoid obstacles and maintain formation in unknown environment, a cooperative formation obstacle avoidance control algorithm based on the improved virtual spring model is proposed.The virtual spring model is introduced on the basis of leader-follower formation approach, which solves the problems of easy touch and out of formation. The attractive elastic force formula between the robot and the target point is established, and the virtual spring model of the obstacle with adjustable damping is designed to complete the obstacle avoidance behavior of robot. Aiming at some complex concave obstacles, the concept of additional …

Learning Variable Neighborhood Search Algorithm For Transportation-Assembly Collaborative Optimization Problem, Tengfei Zhang, Rong Hu, Bin Qian, Lü Yang

Journal of System Simulation

Aiming at transportation-assembly collaborative optimization problems,an integer programming model is established, and a learning variable neighborhood search with decomposition strategy (LVNS_DS) is proposed. To reduce the difficulty of solving the problem, a decomposition strategy is designed to decompose the original problem into a path planning problem and an assembly line balance problem. LVNS is used to solve the two subproblems, and the subproblem solutions are merged to obtain the complete solution of the original problem.Compared with the conventional VNS, LVNS transforms the neighborhood structure according to the neighborhood action probability value, and dynamically updates the probability value according …

Golden Eagle Optimizer Algorithm Combining Levy Flight And Brownian Motion, Jiaxin Deng, Damin Zhang, Qing He, Jianping Zhao

Journal of System Simulation

Aiming at the slow attenuation and low convergence precision of golden eagle optimization algorithm, a new algorithm combining Levy fight and Brownian motion is proposed.In order to increase the diversity, Fuch chaotic map is introduced to initialize the golden eagle individuals. Levy flight mechanism and Brownian motion mechanism are introduced into the position update formula of golden eagle individual to improve the search accuracy and help to the jump out of local optimum. The reduction factor is introduced into the overall position update formula of the golden eagle individual to improve the convergence speed. Compared with 9 original …

Evolution Analysis Of Manufacturing Supply Chain Layout Considering Import Tax Burden And Customs Clearance Delay, Wuqiang Li

Journal of System Simulation

For foreign suppliers located in the special customs supervision area of free trade zone (FTZ), they can avoid the import tax burden of the remaining inventory can be avoided, but the import clearance may affect the timeliness of supply.Considering the widespread application of pull production, evolutionary game is introduced to study the influence of import tax burden and customs clearance delay on supply chain layout in FTZ. Three evolutionary stability strategies (ESS) are researched, which can be determined by the three conditions constructed by the import tax burden and customs clearance delay. The impact of import tax burden …

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 …

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 …

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 …

Predicting Location And Training Effectiveness (Plate), Erik Rolf Bruenner

Master's Theses

Abstract Predicting Location and Training Effectiveness (PLATE)
Erik Bruenner

Physical activity and exercise have been shown to have an enormous impact on many areas of human health and can reduce the risk of many chronic diseases. In order to better understand how exercise may affect the body, current kinesiology studies are designed to track human movements over large intervals of time. Procedures used in these studies provide a way for researchers to quantify an individual’s activity level over time, along with tracking various types of activities that individuals may engage in. Movement data of research subjects is often collected through …

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Accelerating Parameter Identifiability Of Differential Models With Applications To Parameter Estimation, Ilia Ilmer

Dissertations, Theses, and Capstone Projects

The task of mathematical modeling involves working with real world phenomena described via parametric ordinary differential equations (ODE). Typically, an ODE model consists of states, parameters, inputs, and outputs. The states represent quantities whose dynamics the model describes, the parameters are quantities that are specific to the phenomenon being studied. Finally, inputs and outputs represent functions that are being added and measured from experiments, respectively. One of the questions that arises in studies of such models, is whether for given input-output setup one can efficiently and correctly estimate the values of parameters or initial conditions. This property of parameters or …

Imitating Opponent To Win: Adversarial Policy Imitation Learning In Two-Player Competitive Games, The Viet Bui, Tien Mai, Thanh H. Nguyen

Research Collection School Of Computing and Information Systems

Recent research on vulnerabilities of deep reinforcement learning (RL) has shown that adversarial policies adopted by an adversary agent can influence a target RL agent (victim agent) to perform poorly in a multi-agent environment. In existing studies, adversarial policies are directly trained based on experiences of interacting with the victim agent. There is a key shortcoming of this approach --- knowledge derived from historical interactions may not be properly generalized to unexplored policy regions of the victim agent, making the trained adversarial policy significantly less effective. In this work, we design a new effective adversarial policy learning algorithm that overcomes …

Ldptrace: Locally Differentially Private Trajectory Synthesis, Yuntao Du, Yujia Hu, Zhikun Zhang, Ziquan Fang, Lu Chen, Baihua Zheng, Yunjun Gao

Research Collection School Of Computing and Information Systems

Trajectory data has the potential to greatly benefit a wide-range of real-world applications, such as tracking the spread of the disease through people's movement patterns and providing personalized location-based services based on travel preference. However, privacy concerns and data protection regulations have limited the extent to which this data is shared and utilized. To overcome this challenge, local differential privacy provides a solution by allowing people to share a perturbed version of their data, ensuring privacy as only the data owners have access to the original information. Despite its potential, existing point-based perturbation mechanisms are not suitable for real-world scenarios …

Improving The Efficiency Of Exponential Ratio-Type Estimator For Population Median: A Calibration Weight Adjustment Approach, Mathew J. Iseh, Kufre J. Bassey

CBN Journal of Applied Statistics (JAS)

This paper modifies the Bahl and Tuteja exponential ratio-type estimator for population median under simple random and stratified sampling schemes using calibration weight adjustment technique with supplementary information to vary the stratum weights. The bias and mean square error of the modified estimator were obtained up to the second-order approximation, which satisfies the necessary conditions for efficiency. The findings show that the new estimator surpasses existing estimators in efficiency gain. This suggests the appropriateness of calibration weight modification in boosting the efficiency of a population parameter estimator under stratified random sampling especially where the population parameter of the auxiliary variable …

Gnnlens: A Visual Analytics Approach For Prediction Error Diagnosis Of Graph Neural Networks., Zhihua Jin, Yong Wang, Qianwen Wang, Yao Ming, Tengfei Ma, Huamin Qu

Research Collection School Of Computing and Information Systems

Graph Neural Networks (GNNs) aim to extend deep learning techniques to graph data and have achieved significant progress in graph analysis tasks (e.g., node classification) in recent years. However, similar to other deep neural networks like Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), GNNs behave like a black box with their details hidden from model developers and users. It is therefore difficult to diagnose possible errors of GNNs. Despite many visual analytics studies being done on CNNs and RNNs, little research has addressed the challenges for GNNs. This paper fills the research gap with an interactive visual analysis …

Machine Learning And Network Embedding Methods For Gene Co-Expression Networks, Niloofar Aghaieabiane

Dissertations

High-throughput technologies such as DNA microarrays and RNA-seq are used to measure the expression levels of large numbers of genes simultaneously. To support the extraction of biological knowledge, individual gene expression levels are transformed into Gene Co-expression Networks (GCNs). GCNs are analyzed to discover gene modules. GCN construction and analysis is a well-studied topic, for nearly two decades. While new types of sequencing and the corresponding data are now available, the software package WGCNA and its most recent variants are still widely used, contributing to biological discovery.

The discovery of biologically significant modules of genes from raw expression data is …

Domain Decomposition Methods For Linear And Non-Linear Elliptic Problems, Tadanaga Takahashi

Dissertations

The primary purpose of this dissertation is to expand upon the circle of domain decomposition methods (DDM) which are algorithms that reformulate a boundary value problem in terms of multiple localized problems on subdomains. The first project involves expanding upon DDMs in a relatively mature field: the Helmholtz equation for wave scattering applications. The proposed method is an adaptation of a continuous cross-point Finite Element Non-overlapping DDM algorithm. The usual unbounded computational domain is truncated and then the near-field wave pattern is solved with a parallelized finite element method. Several improvements over the standard transmission operator are discussed in this …

Covid-19 In Casinos: Analysis Of Covid-19 Contamination And Spread With Economic Impact Assessment, Anastasia (Stasi) D. Baran, Jason D. Fiege

International Conference on Gambling & Risk Taking

Abstract:

The COVID-19 pandemic caused tremendous disruption for casinos, with the virus causing various lengths of shutdowns, capacity restrictions, and social distancing strategies such as machine removals or section closures. Although most of the world has now eased off these measures, it is important to review lessons learned to understand, and better prepare for similar circumstances in the future. We present Monte Carlo slot floor simulation software customized to simulate players spreading COVID-19 on the slot floor. We simulate the amount of touch surface contamination; the number of potential surface contact exposure events per day, and a proximity exposures statistic …

Statistical Methods To Generate Artificial Slot Floor Data For The Advancement Of Casino Related Research, Courtney Bonner, Anastasia (Stasi) D. Baran, Jason D. Fiege, Saman Muthukumarana

International Conference on Gambling & Risk Taking

Abstract:

A common difficulty when researching gambling topics is the availability of high-quality data sets for development and testing. Due to the high level of secrecy within the gambling industry, if data is obtained for research purposes it is often prohibitively obfuscated, incomplete, or aggregated. Although these data have allowed for advancement in academic work, it leaves both the researchers and readers left wondering about what would be possible if more detailed data sets were available. To mitigate the paucity of data available to researchers, we present a Markov chain-based statistical process for producing artificial event data for a simulated …

The Locals Casino As A Social Network – Can An Interconnected Community Of Players Detect Differences In Hold?, Jason D. Fiege, Anastasia (Stasi) D. Baran

International Conference on Gambling & Risk Taking

Abstract

It is difficult for individual players to detect differences in theoretical hold between slot machines without playing an unrealistically large number of games. This difficulty occurs because the fractional loss incurred by a player converges only slowly to the theoretical hold in the presence of volatility designed into slot pay tables. Nevertheless, many operators believe that players can detect changes in hold or differences compared to competition, especially in a locals casino market, and therefore resist increasing holds. Instead of investigating whether individual players can detect differences in hold, we ask whether a population of casino regulars who share …

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 …

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 …

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 …

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, …

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 …

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 …

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 …

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, …

Auxiliary Decision-Making Method For Flight Support Force Allocation Based On Dbn, Junyang Liu, Shisong Zhu

Journal of System Simulation

Abstract: In order to make up for the deficiency of decision-making methods of full deployment and proportional allocation in airport flight support activities, an auxiliary decision-making model for airport flight support force allocation based on a dynamic Bayesian network (DBN) is constructed.On the basis of quantifying the strength of the support force, thehidden Markov model and Hausdorff distance algorithm are introduced to make auxiliary decisions for flight support activities under different conditions and define relevant decision evaluation indexes as the basis for model verification. Simulation tests are carried out on airport flight support activities under two …

Two-Stage Distributed Robust Optimal Dispatching For A Combined Heat And Power Virtual Power Plant, Yaqian Fan, Songyuan Yu, Fang Fang

Journal of System Simulation

Abstract: Combined heat and power virtual power plant (CHP-VPP) aggregates various electrical and thermal output units and takes into account the uncertainty of wind and solar output, dynamic electricity prices, thermal comfort of users, and other influences to achieve optimal dispatching of overall output. A two-stage distributed robust optimal dispatching method is proposed. In the first stage, planned dispatching is considered, so as to maximize the benefit of CHP-VPP. In the second stage, a fuzzy set of wind and solar output uncertainties is constructed based on the distributed robust method of moment uncertainty, and …

Multi-Camera Vehicle Recognition Method Based On Feature Robustness Enhancement, Huicheng Luo, Shujuan Wang

Journal of System Simulation

Abstract: Due to factors such as viewpoint changes, complex environments, and pose differences under multiple cameras, the images of the same vehicle in different scenes show huge appearance ambiguity, which brings challenges to vehicle identity matching. In order to solve this problem, a feature robustness enhancement method for vehicle recognition is proposed under the transformer framework. Based on the fact that the structural information of the vehicle is invariant under multiple cameras, a module for enhancing structural information guided by contour features is designed, and a structural feature perception loss is proposed to promote the fusion …