Numerical Analysis and Scientific Computing Commons^™

Track Synthetic Algorithm Based On Modified Fuzzy Theory And D-S Evidence Decision, Zhiwei Wang, Yulan Hu, Shujie Hu, Liu Wei

Journal of System Simulation

Abstract: Aiming at the problems existing in fuzzy reasoning track association, such as the filter divergence, the membership performance degradation, the difficulty in determining association threshold value, and the association effect deterioration under complex circumstances, a track association algorithm based on modified fuzzy theory and D-S Evidence Decision is proposed. Based on the attenuated memory extended Kalman filter (AMEKF), a logarithmic likelihood function adaptive correction method is proposed to correct the disorientation of membership function,and a D-S evidence decision-making tracking association algorithm with conflict resolution and consistent focusing is proposed. The simulation results show that comparing with the original algorithm, …

Research On Topology Mapping Method For Multiscale Integration Network Emulation, Liu Yuan, Changling Qiu, Xiaofeng Wang, Jiang Min

Journal of System Simulation

Abstract: For large-scale and scalable network emulation requirements, multi-scale integration emulation based on lightweight virtualization and full virtualization is the trend. In order to take into account the advantages of both virtualizations and enhance the performance of network emulation, a topology mapping method (TMMI) is proposed for multi-scale integration network emulation. This method divides the network topology into lightweight virtualization mapping area and integration virtualization mapping area, and according to different mapping areas uses the optimized multi-level partitioning method to map the network topology reasonably. Experiments show that the proposed method can effectively balance the load and communication overhead …

A Hierarchical Integrated Soft Sensing Modeling Method For Gauss Process Regression, Zhao Shuai, Xudong Shi, Weili Xiong

Journal of System Simulation

Abstract: Chemical processes are often characterized by nonlinearity and multi-phase, a soft sensor model based on the hierarchical ensemble of Gaussian process regression is proposed. First, the Gaussian mixture model is used to divide the process data into different operation phases. Then, the principal component analysis of each stage is carried out, and the model data are divided into several subspaces, according to the contribution of each auxiliary variable in the principal component space, and the corresponding Gaussian process regression model is built. The subspace model output is fused by means to obtain the first level ensemble output. Finally, the …

Research On Fuzzy Adaptive Somatosensory Algorithm For Flight Simulator, Wang Hui, Baofeng Zhang

Journal of System Simulation

Abstract: In order to improve the dynamic fidelity of flight simulator and make full use of the working space, the corresponding improvement scheme of the classical washout algorithm is proposed based on the Stewart motion platform. A two-way fuzzy adaptive elution algorithm is proposed.The algorithm is more in line with the sensory model of the human body by combining the two-way filtering algorithm improvement and the one-dimensional fuzzy adaptive adjustment to compensate the displacement of the high-pass acceleration channel according to the fuzzy rule. The results show that the improved two-way fuzzy adaptive filtering algorithm improves the displacement space from …

Study On Ecological Compensation Of Three Gorges Basin Based On Evolutionary Game Theory, Guangming Yang, Yanjun Shi

Journal of System Simulation

Abstract: Under the background of the green development of the Yangtze River Economic Belt, based on the evolutionary game theory, the game model of the upstream and downstream governments of the Three Gorges Basin and the central ecological compensation behavior are constructed to analyze the interests appeal and compensation behaviors among the three parties, so as to have a complex interest game relationship in the Yangtze River and analyze the cases of ecological compensation in the Three Gorges Basin. The research shows that without the restriction of central government, it is difficult for the upstream and downstream governments in the …

Research On Vibration Characteristics And Parameters Influence Of A Nonlinear Vibration Absorber, Lilan Liu, Bolin Ren, Guodong Zhu

Journal of System Simulation

Abstract: The bistable nonlinear electromagnetic vibration energy harvester (BNEVEH) is used as a vibration absorber to absorb harmful vibration and transfer it into useful electric energy. The mechanical model and governing equation of the main system with BNEVEH are established. The effect of Gauss white noise intensity on large amplitude motion is analyzed by simulations. And the effect law of mass ratio and tuning frequency ratio on the vibration reduction of the main system and power generation of bistable vibration absorber under Gauss white noise excitation is analyzed from the point of vibration reduction and vibration energy harvesting. The optimal …

Low-Complexity Signal Detection Algorithm Based On Pgqsm, Fatang Chen, Yang Kang, Yongli Fu, Mengjie Li

Journal of System Simulation

Abstract: Pre-coding aided Generalized Quadrature Spatial Modulation (PGQSM) uses the known channel state information to perform pre-coding processing on the in-phase and quadrature signals of the quadrature spatial modulation (QSM), so as to reduce the complexity of the receiver for signal detection. At the same time, an improved Pre-coding aided Generalized Quadrature Spatial Modulation low complexity detection algorithm is proposed to solve the problem of the proposed algorithm’s high complexity at the receiver. The results of analysis and simulation show that the proposed algorithm can achieve almost the same BER performance as the maximum likelihood (ML) algorithm with more than …

Optimized Linear Adrc Control For A Class Of Fractional-Order Chaotic Systems, Huang Yu, Xie Tian, Wu Rui

Journal of System Simulation

Abstract: Linear active disturbance rejection control has many parameters and it is difficult to obtain appropriate parameters. Therefore, a quantum-behaved particle swarm optimization algorithm based on cosine decreasing function is proposed in this article for searching optimal LADRC parameters. In this algorithm, cosine decreasing function and updated equation of quantum-behaved particle swarm optimization algorithm are combined. By using the variable characteristic of cosine decreasing function with the increase of iteration times, the original global optimization ability of quantum particle swarm optimization is retained and its poor local optimization ability is overcome. And the simulation results show that the LADRC optimized …

Gcps Adaptive Scheduling Model Based On Cooperative Executor, Zhang Jing, Chen Yao, Sun Jun, Hongbo Fan

Journal of System Simulation

Abstract: Aiming at the problem that the uncertainty of grid cyber physical systems leads to chain failure, an adaptive GCPS dispatching model based on co-actuator is established. First, the constraint conditions of the system are analyzed. A model constraints of GCPS system is presented to describe the constraint conditions of the power system, and it is proved that it meets the consistency of the measure and representing methods. Second, the optimal value of approximation error is solved by PILOT, and the framework of CA-SADM is described. Finally, the performance index, output power accuracy and the influence of fault on the …

Analysis On The Mission Reliability For Auv Based On Monte Carlo Method, Li Juan, Kunyu Zhang, Haibo Li, Lijuan Yang, Mengdi Wang

Journal of System Simulation

Abstract: The high reliability of AUV is the necessary condition for it to complete the task satisfactorily and efficiently within the specified time. Traditional fault tree is very convenient for describing the reliability model of the system, but for large and complex system, this will significantly increase the computation of reliability parameters, thus the calculation is difficult. Because it to calculate the reliability parameters of complex systems by the traditional fault tree, this paper adopts the method of combining the minimum cut set of fault tree and Monte Carlo method to establish the reliability model for Underwater Autonomous Unmanned Vehicle …

Dynamic Inventory Routing Optimization Based On Deep Reinforcement Learning, Jianpin Zhou, Shuliu Zhang

Journal of System Simulation

Abstract: Aiming at the dynamic stochastic inventory routing problem with periodic fluctuation of demand, a novel simulation optimization approach based on deep reinforcement learning is proposed to achieving periodic steady strategy. Firstly a dynamic combinatorial optimization model is constructed. Then, by deep reinforcement learning and setting heuristic rules, the replenishment nodes set selection and the replenishment batch allocation weights in each period are determined. The simulation experimental results show that the proposed method can improve the average profit of a cycle by about 2.7% and 3.9% in low fluctuating demand case and by about 8.2% and 7.1% in high fluctuating …

Corner Localization In Digital Images Based On Radon Transform, Xuguang Wang, Zhang Qin, Su Jie

Journal of System Simulation

Abstract: Location accuracy is one of the key indexes of measuring the performance of feature point.. High location accuracy feature point detection has important implications for the applications such as 3D reconstruction, motion estimation, target tracking and recognition, image registration, etc. A corner location algorithm based on Radon transform is proposed.Edge binary images are obtained with traditional method first, ideal straight lines and curves are extracted then, potential corner locations are calculated next, fake corners are rejected finally. Experimental results on both simulation and real images show that, this method performs better than the existing methods on interest point localization …

Image Restoration Using Automatic Damaged Regions Detection And Machine Learning-Based Inpainting Technique, Chloe Martin-King

Computational and Data Sciences (PhD) Dissertations

In this dissertation we propose two novel image restoration schemes. The first pertains to automatic detection of damaged regions in old photographs and digital images of cracked paintings. In cases when inpainting mask generation cannot be completely automatic, our detection algorithm facilitates precise mask creation, particularly useful for images containing damage that is tedious to annotate or difficult to geometrically define. The main contribution of this dissertation is the development and utilization of a new inpainting technique, region hiding, to repair a single image by training a convolutional neural network on various transformations of that image. Region hiding is also …

A Data Analysis Of The World Happiness Index And Its Relation To The North-South Divide, Charles Alba

Undergraduate Economic Review

In this document, we perform a detailed data analysis on the World Happiness Report with its relation to the socio-economic North-South Divide. In order to do so, we perform some extensive data cleaning and analysis before querying on the World Happiness Report. Our results based on Hypothesis Testing determines the happiness of the Global North is greater than that of the Global South. Furthermore, our queries show that the mean happiness score for the Global North significantly outweighing that of the South. Likewise, the 10 'Happiest' nations all belong to the Global North whereas the 10 'least happy' nations belong …

Incorporating Word Order Explicitly In Glove Word Embedding, Brandon Cox

Computer Science and Computer Engineering Undergraduate Honors Theses

Word embedding is the process of representing words from a corpus of text as real number vectors. These vectors are often derived from frequency statistics from the source corpus. In the GloVe model as proposed by Pennington et al., these vectors are generated using a word-word cooccurrence matrix. However, the GloVe model fails to explicitly take into account the order in which words appear within the contexts of other words. In this paper, multiple methods of incorporating word order in GloVe word embeddings are proposed. The most successful method involves directly concatenating several word vector matrices for each position in …

Developing A Computational Framework For A Construction Scheduling Decision Support Web Based Expert System, Feroz Ahmed

Dissertations

Decision-making is one of the basic cognitive processes of human behaviors by which a preferred option or a course of action is chosen from among a set of alternatives based on certain criteria. Decision-making is the thought process of selecting a logical choice from the available options. When trying to make a good decision, all the positives and negatives of each option should be evaluated. This decision-making process is particularly challenging during the preparation of a construction schedule, where it is difficult for a human to analyze all possible outcomes of each and every situation because, construction of a project …

The R Journal (December 2019) 11(2): Complete Issue, The R Foundation

The R Journal

Editorial, Michael J. Kane

Contributed Research Articles

Using Web Services to Work with Geodata in R, Jan-Philipp Kolb

orthoDr: Semiparametric Dimension Reduction via Orthogonality Constrained Optimization, Ruoqing Zhu, Jiyang Zhang, Ruilin Zhao, Peng Xu, Wenzhuo Zhou, and Xin Zhang

coxed: An R Package for Computing Duration-Based Quantities from the Cox Proportional Hazards Model, Jonathan Kropko and Jeffrey J. Harden

Modeling Regimes with Extremes: The Bayesdfa Package for Identifying and Forecasting Common Trends and Anomalies in Multivariate Time-Series Data, Eric J. Ward, Sean C. Anderson, Luis A. Damiano, Mary E. Hunsicker, and Michael A. Litzow

Fitting Tails by the Empirical Residual …

R Foundation News, Torsten Hothorn

The R Journal

Membership fees and donations received between 2019-09-05 and 2020-02-24.

Conference: Report Conectar 2019, Marcela Alfaro Córdoba, Frans Van Dunné, Agustín Gómez Meléndez, Jacob Van Etten

The R Journal

ConectaR 2019: Encuentro de Usuarios R en Latinoamérica, took place during January 24-26, 2019 at the University of Costa Rica, in San José, Costa Rica. It was the first event in Central America endorsed by The R Foundation, and it was held completely in Spanish. The majority of the attendants were from Costa Rica (85%), but we had participants from 12 countries: Costa Rica, Guatemala, Peru, Colombia, Mexico, Argentina, Uruguay, Chile, Spain, the Netherlands, France and the USA. The three-day event consisted of talks, workshops, and poster sessions.

Lpirfs: An R Package To Estimate Impulse Response Functions By Local Projections, Philipp Adämmer

The R Journal

Impulse response analysis is a cornerstone in applied (macro-)econometrics. Estimating impulse response functions using local projections (LPs) has become an appealing alternative to the traditional structural vector autoregressive (SVAR) approach. Despite its growing popularity and applications, however, no R package yet exists that makes this method available. In this paper, I introduce lpirfs, a fast and flexible R package that provides a broad framework to compute and visualize impulse response functions using LPs for a variety of data sets.