Numerical Analysis and Scientific Computing Commons^™

Study On Pulverizing System Simulation Model Of 300mw Lignite Oxygen-Enriched Combustion Boiler, Jianqiang Gao, Shaodong Sun

Journal of System Simulation

Abstract: The simulation model of the pulverizing system of a 300 MW lignite oxygen-enriched combustion boiler was developed. And the dynamic and static simulation experiments were completed, the experiments included lignite surface moisture content variation, disturbance of feeder norm speed, flue gas inlet temperature and flow rate etc. The results show that, the model is able to correctly simulate the dynamic process of the system. Moisture reduction has a larger impact on the pulverizing system operating parameters. The mill outlet temperature gets a significant rise, especially when it is less than 30%. When the feeder norm speed or flow rate …

Thermal Power Plants Main Steam Temperature System Control Based On Implicit Pigpc, Zhongda Tian, Shujiang Li, Yanhong Wang

Journal of System Simulation

Abstract: Aiming at the large inertial time-delay characteristic of main steam temperature control system on the thermal power plants, a control method based on Implicit PI-based generalized predictive controller (GPC) was proposed. The implicit PIGPC algorithm with PI structure was proposed based on implicit GPC, implicit PI-based GPC combined the advantages of PI control and implicit GPC, the feedback structure of PI and prediction function of GPC was combined. The predictive control algorithm with PI structure was obtained through a new objective function, the performance of controller was improved. At the same time, the stability of the compensation algorithm was …

Key Technology Of Fully Immersive Virtual Experience Cabin, Baojiang Du, Zha Liang, Lin Ling

Journal of System Simulation

Abstract: The structure of simulated experience cabin for fire safety education was introduced and the design and implementation methods of a virtual fire escape system for fire safety education were proposed, and specifically the specific implementation and optimization of virtual fire scenario, the conjunction method of double virtual interactive platforms and the simplification of model and the method of communication between the virtual scenes and the PLC control hardware devices were discusses. Fire safety education oriented virtual fire escape skills training system was achieved, which was applied in the teaching and experience room for fire safety training. Application results show …

Research Of Vibration Control On Nonlinear Rotor System With Fuzzy-Pid, Liu Jun, Zhenwang Liu, Jianen Chen, Liangfu Wang

Journal of System Simulation

Abstract: In order to overcome the problems which are the model of the nonlinear restoring force and the nonlinear vibration control, the vibration control of the nonlinear rotor system and the processing the nonlinear restoring force were accomplished based on the electromagnetic actuator using the FUZZY-PID controller with the fitness function of the variable width and variable geometric shapes. Using the Jeffcott rotor model with the nonlinearities of the forces of the bearing and the electromagnetic actuator, the simulations of the vibration control on the rotor system were performed. Through comparing with the control methods of the traditional PID and …

Simulation And Evaluation Of Facility Layout In Environment With Complexity For Manufacturing System, Ailin Yu, Qingxin Chen, Mao Ning

Journal of System Simulation

Abstract: To research the performance for manufacturing system of equipment with different layout of facility, a method of simulation and evaluation in the environment with complexity of manufacturing system was proposed. Three kinds of typical layout of facility were concluded and abstract by the enterprise facts. The evaluation system was established in the environment with complexity of manufacturing system. The construction method of the entropy models were described emphatically. Simulation models were developed based on the production and process model. The layouts were analyzed and evaluated by the data of the evaluation system from simulation experiments.

Optimal Design Of High Power Medium Frequency Transformer Based On Channel Lightweight Requirement, Fangcheng Lü, Yunxiang Guo, Li Peng

Journal of System Simulation

Abstract: The analytical calculation method for winding loss and core loss of high power medium frequency transformer was analyzed, and the optimal design process was established. A 300 kW medium frequency transformer for lightweight application of electric locomotive was designed optimally by the method of free parameters scanning. Through the establishment of evaluation parameters equation, the best scheme considered both the total loss and transformer weight. On this basis, the winding loss and core loss for six groups of design scheme were verified by finite element simulation in 2D eddy current field and transient field of Ansoft Maxwell respectively. Through …

Steering Dynamics Simulation Analysis Of Replaceable Triangular Track Of Skidder, Xiaowen Ge, Jiejian Hou, Lihai Wang

Journal of System Simulation

Abstract: In order to design a kind of high efficiency and low cost multifunctional skidder suitable for forest conditions of China, the replaceable triangular track was applied to skidder and the virtual prototype of triangular track skidder and road models were built based on the theoretical analysis by Solidworks and RecurDyn Software. Simulation analysis regarding the effects of pre-tension, turning angle, road conditions, loading and skidding on skidder's turning performance was made. Research results show that the pre-tension of 19.2 kN (40% of the vehicle weight) is much proper for turning. The larger turning angle is, the easier skidder turned, …

Ari: The Automated R Instructor, Sean Kross, Jeffrey T. Leek, John Muschelli

The R Journal

We present the ari package for automatically generating technology-focused educational videos. The goal of the package is to create reproducible videos, with the ability to change and update video content seamlessly. We present several examples of generating videos including using R Markdown slide decks, PowerPoint slides, or simple images as source material. We also discuss how ari can help instructors reach new audiences through programmatically translating materials into other languages.

The R Journal (June 2020) 12(1): Complete Issue, The R Foundation

The R Journal

Editorial, Michael J. Kane

Contributed Research Articles

gk: An R Package for the g-and-k and Generalised g-and-h Distributions, Dennis Prangle

NlinTS: An R Package for Causality Detection in Time Series, Youssef Hmamouche

Mapping Smoothed Spatial Effect Estimates from Individual-Level Data: MapGAM, Lu Bai, Daniel L. Gillen, Scott M. Bartell, and Verónica M. Vieira

mudfold: An R Package for Nonparametric IRT Modelling of Unfolding Processes, Spyros E. Balafas, Wim P. Krijnen, Wendy J. Post, and Ernst C. Wit

tsmp: An R Package for Time Series with Matrix Profile, Francisco Bischoff and Pedro Pereira Rodrigues

Individual-Level Modelling of Infectious Disease Data: EpiILM, …

Modeling And Analysis Of Trust Attack Based On Object-Oriented Petri Net, Guangqiu Huang, Bai Lu

Journal of System Simulation

Abstract: On the basis of trust attack graph, the object-oriented trust attack Petri net model was put forward, the dynamic model described the attack behaviors among components of trust entity object. By introducing the object Petri net, the trust attack relations between trust entity objects and components were shown in the Petri net, simulating the collaborative work between the components. According to the new trust relation reconstruction rules, a trust attack path inference algorithm was proposed to make the attacker knowing the changes of harmfulness when attacking the components, thus the attacker could decide the attack direction. The maximal …

Genetic Algorithm For Solving Multi-Objective Dynamic Flexible Job Shop Scheduling, Wang Chun, Zhang Ming, Zhicheng Ji, Wang Yan

Journal of System Simulation

Abstract: To solve the scheduling problem of mold workshop in a toy factory with dynamic and flexible features, a mathematical model was established by introducing virtual operation and virtual working hours. Based on the strategies of periodic scheduling combined with dynamic event scheduling as well as the rolling window scheduling operation technology, dynamic scheduling was transformed into several continuous static scheduling windows, under which multi-objective genetic algorithm was used to solve the model. The priority of operation scheduling was given in different dynamic events. In addition, the encoding and anti-encoding of chromosome's operation sequence were made based on the proposed …

Improved Particle Swarm Optimization Based On Lévy Flights, Rongyu Li, Wang Ying

Journal of System Simulation

Abstract: The particle swarm optimization (PSO) has some demerits, such as relapsing into local extremum, slow convergence velocity and low convergence precision in the late evolutionary. The Lévy particle swarm optimization (Lévy PSO) was proposed. In the particle position updating formula, Lévy PSO eliminated the impact of speed on the convergence rate, and used Levy flight to change the direction of particle positions movement to prevent particles getting into local optimum value, and then using greedy strategy to update the evaluation and choose the best solution to obtain the global optimum. The experimental results show that Lévy PSO can effectively …

Study On Secrecy Capacity Of Wireless Sensor Networks Based On Amplify-And-Forward Compressed Sensing Scheme, Jianlan Guo, Yuqiang Chen, Yijun Liu

Journal of System Simulation

Abstract: Due to the limitation of wireless sensor nodes on computation, power energy and storage space, the security issue has become a prevalent concern in the wireless communication. A deep insight on the secrecy capacity of wireless sensor network based on the Amplify-and-Forward (AF) compressed sensing scheme was offered providing a corresponding calculable capacity threshold. Moreover, a feasible algorithm based on augmented Lagrange method for the reconstruction of communication signals was proposed. Furthermore, the impact of the secrecy capacity was discussed to various numbers of active sensor nodes, relay nodes and eavesdropper nodes. Simulation results demonstrate the validity of the …

Provenance Of R’S Gradient Optimizers, John C. Nash

The R Journal

Gradient optimization methods (function minimizers) are well-represented in both the base and package universe of R (R Core Team, 2019). However, some of the methods and the codes developed from them were published before standards for hardware and software were established, in particular the IEEE arithmetic (IEEE, 1985). There have been cases of unexpected behaviour or outright errors, and these are the focus of the histoRicalg project. A summary history of some of the tools in R for gradient optimization methods is presented to give perspective on such methods and the occasions where they could be used effectively.

S, R, And Data Science, John M. Chambers

The R Journal

Data science is increasingly important and challenging. It requires computational tools and programming environments that handle big data and difficult computations, while supporting creative, high-quality analysis. The R language and related software play a major role in computing for data science. R is featured in most programs for training in the field. R packages provide tools for a wide range of purposes and users. The description of a new technique, particularly from research in statistics, is frequently accompanied by an R package, greatly increasing the usefulness of the description.

The history of R makes clear its connection to data science. …

The Rockerverse: Packages And Applications For Containerisation With R, Daniel Nüst, Dirk Eddelbuettel, Dom Bennett, Robrecht Cannoodt, Dav Clark, Gergely Daróczi, Mark Edmondson, Colin Fay, Ellis Hughes, Lars Kjeldgaard, Sean Lopp, Ben Marwick, Heather Nolis, Jacqueline Nolis, Hong Ooi, Kathik Ram, Noam Ross, Lori Shepard, Péter Sólymos, Tyson Lee Swetnam, Nitesh Turaga, Charlotte Van Petegem, Jason Williams, Craig Willis, Nan Xiao

The R Journal

The Rocker Project provides widely used Docker images for R across different application scenarios. This article surveys downstream projects that build upon the Rocker Project images and presents the current state of R packages for managing Docker images and controlling containers. These use cases cover diverse topics such as package development, reproducible research, collaborative work, cloud-based data processing, and production deployment of services. The variety of applications demonstrates the power of the Rocker Project specifically and containerisation in general. Across the diverse ways to use containers, we identified common themes: reproducible environments, scalability and efficiency, and portability across clouds. We …

Linear Fractional Stable Motion With The Rlfsm R Package, Stepan Mazur, Dmitry Otryakhin

The R Journal

Linear fractional stable motion is a type of a stochastic integral driven by symmetric alpha-stable Lévy motion. The integral could be considered as a non-Gaussian analogue of the fractional Brownian motion. The present paper discusses R package rlfsm created for numerical procedures with the linear fractional stable motion. It is a set of tools for simulation of these processes as well as performing statistical inference and simulation studies on them. We introduce: tools that we developed to work with that type of motions as well as methods and ideas underlying them. Also we perform numerical experiments to show finite-sample behavior …

Bayesmallows: An R Package For The Bayesian Mallows Model, Øystein Sørensen, Marta Crispino, Qinghua Liu, Valeria Vitelli

The R Journal

BayesMallows is an R package for analyzing preference data in the form of rankings with the Mallows rank model, and its finite mixture extension, in a Bayesian framework. The model is grounded on the idea that the probability density of an observed ranking decreases exponentially with the distance to the location parameter. It is the first Bayesian implementation that allows wide choices of distances, and it works well with a large amount of items to be ranked. BayesMallows handles non-standard data: partial rankings and pairwise comparisons, even in cases including non-transitive preference patterns. The Bayesian paradigm allows coherent quantification of …

Rcosmo: R Package For Analysis Of Spherical, Healpix And Cosmological Data, Daniel Fryer, Ming Li, Andriy Olenko

The R Journal

The analysis of spatial observations on a sphere is important in areas such as geosciences, physics and embryo research, just to name a few. The purpose of the package rcosmo is to conduct efficient information processing, visualisation, manipulation and spatial statistical analysis of Cosmic Microwave Background (CMB) radiation and other spherical data. The package was developed for spherical data stored in the Hierarchical Equal Area isoLatitude Pixelation (Healpix) representation. rcosmo has more than 100 different functions. Most of them initially were developed for CMB, but also can be used for other spherical data as rcosmo contains tools for transforming spherical …

Lspartition: Partitioning-Based Least Squares Regression, Matias D. Cattaneo, Max H. Farrell, Yingjie Feng

The R Journal

Nonparametric partitioning-based least squares regression is an important tool in empirical work. Common examples include regressions based on splines, wavelets, and piecewise polynomials. This article discusses the main methodological and numerical features of the R software package lspartition, which implements results for partitioning-based least squares (series) regression estimation and inference from Cattaneo and Farrell (2013) and Cattaneo, Farrell, and Feng (2020). These results cover the multivariate regression function as well as its derivatives. First, the package provides data-driven methods to choose the number of partition knots optimally, according to integrated mean squared error, yielding optimal point estimation. Second, robust …

Mudfold: An R Package For Nonparametric Irt Modelling Of Unfolding Processes, Spyros E. Balafas, Wim P. Krijnen, Wendy J. Post, Ernst C. Wit

The R Journal

Item response theory (IRT) models for unfolding processes use the responses of individuals to attitudinal tests or questionnaires in order to infer item and person parameters located on a latent continuum. Parametric models in this class use parametric functions to model the response process, which in practice can be restrictive. MUDFOLD (Multiple UniDimensional unFOLDing) can be used to obtain estimates of person and item ranks without imposing strict parametric assumptions on the item response functions (IRFs). This paper describes the implementation of the MUDFOLD method for binary preferential-choice data in the R package mudfold. The latter incorporates estimation, visualization, …

Mapping Smoothed Spatial Effect Estimates From Individual-Level Data: Mapgam, Lu Bai, Daniel L. Gillen, Scott M. Bartell, Verónica M. Vieira

The R Journal

We introduce and illustrate the utility of MapGAM, a user-friendly R package that provides a unified framework for estimating, predicting and drawing inference on covariate-adjusted spatial effects using individual-level data. The package also facilitates visualization of spatial effects via automated mapping procedures. MapGAM estimates covariate-adjusted spatial associations with a univariate or survival outcome using generalized additive models that include a non-parametric bivariate smooth term of geolocation parameters. Estimation and mapping methods are implemented for continuous, discrete, and right-censored survival data. In the current manuscript, we summarize the methodology implemented in MapGAM and illustrate the package using two example simulated …

Nlints: An R Package For Causality Detection In Time Series, Youssef Hmamouche

The R Journal

The causality is an important concept that is widely studied in the literature, and has several applications, especially when modelling dependencies within complex data, such as multivariate time series. In this article, we present a theoretical description of methods from the NlinTS package, and we focus on causality measures. The package contains the classical Granger causality test. To handle non-linear time series, we propose an extension of this test using an artificial neural network. The package includes an implementation of the Transfer entropy, which is also considered as a non linear causality measure based on information theory. For discrete variables, …

Editorial, Michael J. Kane

The R Journal

Onbehalf of the editorial board, I am pleased to present Volume 12, Issue 1 of the R Journal and mysecond issue as the Editor in Chief. Since the last issue Simon Urbanek has joined the editorial board and we have made a few structural changes. First, the R Foundation has approved the R Journal having Associate Editors. This change will allow us to address the increase in submission volume. The addition of the new AE positions should help alleviate some of the workload the editors have been dealing with and will result in shorter turn-around times for submissions. Second, complete …

Gk: An R Package For The G-And-K And Generalised G-And-H Distributions, Dennis Prangle

The R Journal

The g-and-k and (generalised) g-and-h distributions are flexible univariate distributions which can model highly skewed or heavy tailed data through only four parameters: location and scale, and two shape parameters influencing the skewness and kurtosis. These distributions have the unusual property that they are defined through their quantile function (inverse cumulative distribution function) and their density is unavailable in closed form, which makes parameter inference complicated. This paper presents the gk R package to work with these distributions. It provides the usual distribution functions and several algorithms for inference of independent identically distributed data, including the finite difference stochastic approximation …

Similar: R Code Clone And Plagiarism Detection, Maciej Bartoszuk, Marek Gagolewski

The R Journal

Third-party software for assuring source code quality is becoming increasingly popular. Tools that evaluate the coverage of unit tests, perform static code analysis, or inspect run-time memory use are crucial in the software development life cycle. More sophisticated methods allow for performing meta-analyses of large software repositories, e.g., to discover abstract topics they relate to or common design patterns applied by their developers. They may be useful in gaining a better understanding of the component interdependencies, avoiding cloned code as well as detecting plagiarism in programming classes.

Ameaningful measure of similarity of computer programs often forms the basis of such …

Coxphlb: An R Package For Analyzing Length Biased Data Under Cox Model, Chi Hyun Lee, Heng Zhou, Jing Ning, Diane D. Liu, Yu Shen

The R Journal

Data subject to length-biased sampling are frequently encountered in various applications including prevalent cohort studies and are considered as a special case of left-truncated data under the stationarity assumption. Many semiparametric regression methods have been proposed for length biased data to model the association between covariates and the survival outcome of interest. In this paper, we present a brief review of the statistical methodologies established for the analysis of length-biased data under the Cox model, which is the most commonly adopted semiparametric model, and introduce an R package CoxPhLb that implements these methods. Specifically, the package includes features such as …

The R Package Nonprobest For Estimation In Non-Probability Surveys, M. Rueda, R. Ferri-García, L. Castro

The R Journal

Different inference procedures are proposed in the literature to correct selection bias that might be introduced with non-random sampling mechanisms. The R package NonProbEst enables the estimation of parameters using some of these techniques to correct selection bias in non-probability surveys. The mean and the total of the target variable are estimated using Propensity Score Adjustment, calibration, statistical matching, model-based, model-assisted and model-calibratated techniques. Confidence intervals can also obtained for each method. Machine learning algorithms can be used for estimating the propensities or for predicting the unknown values of the target variable for the non-sampled units. Variance of a given …

Variable Importance Plots: An Introduction To The Vip Package, Brandon M. Bartoszuk, Marek Gagolewski

The R Journal

In the era of “big data”, it is becoming more of a challenge to not only build state-of-the-art predictive models, but also gain an understanding of what’s really going on in the data. For example, it is often of interest to know which, if any, of the predictors in a fitted model are relatively influential on the predicted outcome. Some modern algorithms—like random forests (RFs) and gradient boosted decision trees (GBMs)—have a natural way of quantifying the importance or relative influence of each feature. Other algorithms—like naive Bayes classifiers and support vector machines—are not capable of doing so and model-agnostic …

Tsmp: An R Package For Time Series With Matrix Profile, Francisco Bischoff, Pedro Pereira Rodriques

The R Journal

This article describes tsmp, an R package that implements the MP concept for TS. The tsmp package is a toolkit that allows all-pairs similarity joins, motif, discords and chains discovery, semantic segmentation, etc. Here we describe how the tsmp package may be used by showing some of the use-cases from the original articles and evaluate the algorithm speed in the R environment. This package can be downloaded at https://CRAN.R-project.org/package=tsmp.