Numerical Analysis and Scientific Computing Commons^™

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 …

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 …

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 …

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 …

Simulation Platform For Optimization And Decision Making Of Flexible Manufacturing Process Of Automatic Production Lines, Chao Fu, Dongyue Wang, Xinxin Li, Min Xue

Journal of System Simulation

Abstract: In order to simulate a flexible manufacturing process to verify the correctness of theoretical computation and analysis and find other important factors for optimization and decision making in the manufacturing process, a simulation platform for the optimization and decision making of the flexible manufacturing process of automatic production lines is designed and developed. The framework of the simulation platform is constructed with four hierarchies, including the enterprise production hierarchy, optimization and decision making hierarchy, data resource hierarchy, and function module hierarchy. On this basis, the functional implementation of the modules of production allocation …

Modeling And Simulation Of Spaceborne, Near-Spaceborne, And Airborne Integrated Collaborative Remote Sensing System Based On Dodaf, Lili An, Tian Xia, Wenbin Yang, Xinbo Wu

Journal of System Simulation

Abstract: Spaceborne, near-spaceborne, and airborne integrated collaborative remote sensing system (SNA-ICRSS) makes comprehensive use of modern information technology to aggregate multiple and heterogeneous data in spaceborne, near-spaceborne, and airborne domains, so as to realize accurate emergency service and command decision-making. SNA-ICRSS is huge and complex, and there is a lack of research on its architecture modeling and simulation. According to the architecture characteristics of the SNA-ICRSS, the minimum prototype of the SNA-ICRSS is constructed; through the department of defense architecture framework (DoDAF) and activity based methodology (ABM) methods, the minimal prototype of the SNA-ICRSS is modeled, and the operational resource …

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 …

Partial Task Offloading Strategy Of Cloud Robots Based On Game Theory Under Cloud-Edge Coordination, Chunmao Jiang, Zhenxing Yang

Journal of System Simulation

Abstract: How to rationally utilize the resources of central and edge clouds to reduce energy consumption of system equipment and shorten average task completion time is a fundamental challenge for computational task offloading of cloud robots. In this paper, we transform the computational task offloading problem of multiple cloud robots into a multi-actor game model by using the computational task completion time and energy consumption of cloud robots as cost measurement indicators and setting different cost weights according to actual needs. We also develop a game theory-based partial task offloading algorithm (GT-PTO). With the Nash equilibrium state …

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 …

Research On No-Wait Flow Shop Scheduling Based On Discrete State Transition Algorithm, Jiaying Yu, Hongli Zhang, Yingchao Dong

Journal of System Simulation

Abstract: In view of the no-wait flow shop problem (NWFSP) widely existing in the manufacturing industry, an improved discrete state transition algorithm (IDSTA) is proposed to solve the problem. The coding mode of the workpiece is designed based on the characteristics of the flow shop scheduling problem (FSSP). The initial solution is constructed by the Nawaz-Enscore-Ham (NEH) method with the standard deviation of the processing time of the workpiece as the priority, and a multi-neighborhood combinatorial search strategy based on insertion and exchange is designed to improve the quality of the initial solution. A discrete state transition algorithm ( …

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 …

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 …

Picking Path Planning Of Container Robots Based On Improved Genetic Algorithm, Yuwen Wu, Zhiyue Niu, Zhenping Li

Journal of System Simulation

Abstract: Under the new "container-to-person" picking mode in intelligent warehouses, a new optimization model and its improved genetic algorithm are proposed to solve the picking path planning problem of multiple container robots. According to the picking mode and characteristics of container robots, the picking path planning problem is transformed into an asymmetric vehicle routing problem, and a mixed integer programming model is established with bi-objectives of the shortest total picking path and the least completion time. A hybrid genetic algorithm is designed to solve this model, and the effectiveness and stability of the algorithm are verified …

Action Recognition Method Based On Projection Subspace Views Under Single Viewing Angle, Benyue Su, Manzhen Sun, Qing Ma, Min Sheng

Journal of System Simulation

Abstract: In view of the self-occlusion problem of joint action tracking by a depth camera under a single viewing angle, a new human action recognition method based on projection subspace views is proposed. Without adding data acquisition equipment, the method projects the three-dimensional(3D) action sequences obtained under a single viewing angle into multiple two-dimensional subspacesand then seeks the maximum distance between classes in the two-dimensional subspaces, so as to increase the distance between 3D actions based on the fusion of multiple subspace views as much as possible. The recognition rate in the self-built AQNU …

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 …