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StochSD: A Full Potential CSS Language for Dynamic and Stochastic Modelling, Simulation and Statistical Analysis 随机的动态和随机建模、模拟和统计分析的全潜力CSS语言
Pub Date : 2022-01-01 DOI: 10.4236/ojmsi.2022.102012
L. Gustafsson, E. Gustafsson, M. Gustafsson
It is vital that a well-defined conceptual model can be realized by a macro-model (e.g., a Continuous System Simulation (CSS) model) or a micro-model (e.g., an Agent-Based model or Discrete Event Simulation model) and still produce mutually consistent results. The Full Potential CSS concept provides the rules so that the results from macro-modelling become fully consistent with those from micro-modelling. This paper focuses on the simulation language StochSD (Stochastic System Dynamics), which is an extension of classical Continuous System Simulation that implements the Full Potential CSS concept. Thus, in addition to modelling and simulating continuous flows between compartments represented by “real” numbers, it can also handle transitions of discrete entities by integer numbers, enabling combined models to be constructed in a straight-forward way. However, transition events of discrete entities (e.g., arrivals, accidents, deaths) usually happen irregularly over time, so stochasticity often plays a crucial role in their modelling. Therefore, StochSD contains powerful random functions to model uncertainties of different kinds, together with devices to collect statistics during a simulation or from multiple replications of the same stochastic model. Also, tools for sensitivity analysis, optimisation and statistical analysis are included. In particular, StochSD includes features for stochastic modelling, post-analysis of multiple simulations, and presentation of the results in statistical form. In addition to making StochSD a Full Potential CSS language, sive material for a course in Modelling and Simulation in form of PowerPoint lectures and laboratory exercises.
重要的是,定义良好的概念模型可以通过宏观模型(例如,连续系统仿真(CSS)模型)或微观模型(例如,基于代理的模型或离散事件仿真模型)实现,并且仍然产生相互一致的结果。全潜能CSS概念提供了规则,使宏观建模的结果与微观建模的结果完全一致。本文重点研究了随机系统动力学(Stochastic System Dynamics,随机系统动力学)仿真语言,它是经典连续系统仿真的扩展,实现了全潜能CSS概念。因此,除了建模和模拟用“实数”表示的间隔之间的连续流外,它还可以用整数处理离散实体的转换,从而可以直接构建组合模型。然而,离散实体的过渡事件(例如,到达,事故,死亡)通常随时间不规则地发生,因此随机性通常在其建模中起着至关重要的作用。因此,随机sd包含强大的随机函数来模拟不同类型的不确定性,以及在模拟期间或从同一随机模型的多个复制中收集统计数据的设备。此外,工具的敏感性分析,优化和统计分析包括在内。特别是,随机sd包括随机建模、多次模拟的后期分析和以统计形式表示结果的特征。除了使stacsd成为一个充分发挥潜力的CSS语言之外,它还以PowerPoint讲座和实验练习的形式为建模和仿真课程提供了大量材料。
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引用次数: 0
Application Research on Real-Time Interactive Simulation System of Container Yard Based on Unity3D 基于Unity3D的集装箱堆场实时交互仿真系统应用研究
Pub Date : 2022-01-01 DOI: 10.4236/ojmsi.2022.103016
Rongrong Hu, Xumin Zhou, Yiping Yu
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引用次数: 2
Numerical Simulation and Measurement of Air Temperature and Relative Humidity in an Olive Cuttings Tunnel Greenhouse 橄榄枝隧道温室空气温度和相对湿度的数值模拟与测量
Pub Date : 2022-01-01 DOI: 10.4236/ojmsi.2022.101002
Sanae Chakir, A. Bekraoui, H. Majdoubi, A. Senhaji, M. Mouqallid
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引用次数: 0
Computational Analysis for Solving the Linear Space-Fractional Telegraph Equation 求解线性空间-分数阶电报方程的计算分析
Pub Date : 2022-01-01 DOI: 10.4236/ojmsi.2022.103014
Z. M. Alaofi, T. El-Danaf, Adel R. Hadhoud, S. Dragomir
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引用次数: 0
Bayesian Variable Selection for Mixture Process Variable Design Experiment 混合工艺变量设计实验的贝叶斯变量选择
Pub Date : 2022-01-01 DOI: 10.4236/ojmsi.2022.104022
Sadiah M. A. Aljeddani
This paper discussed Bayesian variable selection methods for models from split-plot mixture designs using samples from Metropolis-Hastings within the Gibbs sampling algorithm. Bayesian variable selection is easy to implement due to the improvement in computing via MCMC sampling. We described the Bayesian methodology by introducing the Bayesian framework, and explaining Markov Chain Monte Carlo (MCMC) sampling. The Metropolis-Hastings within Gibbs sampling was used to draw dependent samples from the full conditional distributions which were explained. In mixture experiments with process variables, the response depends not only on the proportions of the mixture components but also on the effects of the process variables. In many such mixture-process variable experiments, constraints such as time or cost prohibit the selection of treatments completely at random. In these situations, restrictions on the randomisation force the level combinations of one group of factors to be fixed and the combinations of the other group of factors are run. Then a new level of the first-factor group is set and combinations of the other factors are run. We discussed the computational algorithm for the Stochastic Search Variable Selection (SSVS) in linear mixed models. We extended the computational algorithm of SSVS to fit models from split-plot mixture design by introducing the algorithm of the Stochastic Search Variable Selection for Split-plot Design (SSVS-SPD). The motivation of this extension is that we have two different levels of the experimental units, one for the whole plots and the other for subplots in the split-plot mixture design.
本文讨论了分离式混合设计模型的贝叶斯变量选择方法,使用吉布斯抽样算法中的Metropolis-Hastings样本。由于通过MCMC采样改进了计算能力,贝叶斯变量选择易于实现。我们通过介绍贝叶斯框架来描述贝叶斯方法,并解释了马尔可夫链蒙特卡罗(MCMC)抽样。采用Metropolis-Hastings within Gibbs抽样法从已解释的完全条件分布中抽取相关样本。在有工艺变量的混合实验中,响应不仅取决于混合组分的比例,还取决于工艺变量的影响。在许多这样的混合工艺变量实验中,时间或成本等限制因素禁止完全随机选择处理方法。在这种情况下,随机性的限制迫使一组因素的关卡组合被固定,而另一组因素的组合被运行。然后设置第一个因素组的新水平,并运行其他因素的组合。讨论了线性混合模型中随机搜索变量选择的计算算法。通过引入split-plot design随机搜索变量选择算法(SSVS- spd),将SSVS的计算算法扩展到适合分块混合设计模型。这个扩展的动机是我们有两个不同级别的实验单元,一个用于整个地块,另一个用于分裂地块混合设计中的子地块。
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引用次数: 1
Modeling the Nigerian Bonny Light Crude Oil Price: The Power of Fuzzy Time Series 尼日利亚邦尼轻质原油价格建模:模糊时间序列的力量
Pub Date : 2021-08-27 DOI: 10.4236/ojmsi.2021.94024
D. C. Bartholomew, U. C. Orumie, C. P. Obite, Blessing Iheoma Duru, F. C. Akanno
Several authors have used different classical statistical models to fit the Nigerian Bonny Light crude oil price but the application of machine learning models and Fuzzy Time Series model on the crude oil price has been grossly understudied. Therefore, in this study, a classical statistical model—Autoregressive Integrated Moving Average (ARIMA), two machine learning models—Artificial Neural Network (ANN) and Random Forest (RF) and Fuzzy Time Series (FTS) Model were compared in modeling the Nigerian Bonny Light crude oil price data for the periods from January, 2006 to December, 2020. The monthly secondary data were collected from the Nigerian National Petroleum Corporation (NNPC) and Reuters website and divided into train (70%) and test (30%) sets. The train set was used in building the models and the models were validated using the test set. The performance measures used for the comparison include: The modified Diebold-Mariano test, the Root Mean Square Error (RMSE), the Mean Absolute Percentage Error (MAPE) and Nash-Sutcliffe Efficiency (NSE) values. Based on the performance measures, ANN (4, 1, 1) and RF performed better than ARIMA (1, 1, 0) model but FTS model using Chen’s algorithm outperformed every other model. The results recommend the use of FTS model for forecasting future values of the Nigerian Bonny Light Crude oil. However, a hybrid model of ARIMA-ANN or ARIMA-RF should be built and compared with Chen’s algorithm FTS model for the same data set to further verify the power of FTS model using Chen’s algorithm.
几位作者使用了不同的经典统计模型来拟合尼日利亚邦尼轻质原油价格,但机器学习模型和模糊时间序列模型在原油价格上的应用研究严重不足。因此,在本研究中,在对2006年1月至2020年12月尼日利亚邦尼轻质原油价格数据建模时,比较了经典统计模型——自回归综合移动平均值(ARIMA)、两种机器学习模型——人工神经网络(ANN)和随机森林(RF)以及模糊时间序列(FTS)模型。每月的二次数据来自尼日利亚国家石油公司(NNPC)和路透社网站,分为训练集(70%)和测试集(30%)。在建立模型时使用了训练集,并使用测试集对模型进行了验证。用于比较的性能指标包括:修正的Diebold Mariano检验、均方根误差(RMSE)、平均绝对百分比误差(MAPE)和Nash-Sutcliffe效率(NSE)值。基于性能测量,ANN(4,1,1)和RF的性能优于ARIMA(1,1,0)模型,但使用Chen算法的FTS模型的性能优于其他模型。研究结果建议使用FTS模型预测尼日利亚邦尼轻质原油的未来价值。然而,对于相同的数据集,应该建立ARIMA-ANN或ARIMA-RF的混合模型,并与Chen的算法FTS模型进行比较,以进一步验证使用Chen算法的FTS模型的功效。
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引用次数: 2
Theoretical Analysis of the Effect of the Interfacial MoSe2 Layer in CIGS-Based Solar Cells CIGS基太阳能电池界面MoSe2层效应的理论分析
Pub Date : 2021-08-27 DOI: 10.4236/ojmsi.2021.94022
A. Sylla, N’Guessan Armel Ignace, T. Siaka, J. Vilcot
The aim of this work is to analyze the influence of the interfacial MoSe2 layer on the performance of a /n-ZnO/i-ZnO/n-Zn(O,S)/p-CIGS/p+-MoSe2/Mo/SLG solar cell. In this investigation, the numerical simulation software AFORS-HET is used to calculate the electrical characteristics of the cell with and without this MoSe2 layer. Different reported experimental works have highlighted the presence of a thin-film MoSe2 layer at the CIGS/Mo contact interface. Under a tunneling effect, this MoSe2 layer transforms the Schottky CIGS/Mo contact nature into a quasi-ohmic one. Owing to a heavily p-doping, the MoSe2 thin layer allows better transport of majority carrier, tunneling them from CIGS to Mo. Moreover, the bandgap of MoSe2 is wider than that of the CIGS absorbing layer, such that an electric field is generated close to the back surface. The presence of this electric field reduces carrier recombination at the interface. Under these conditions, we examined the performance of the cell with and without MoSe2 layer. When the thickness of the CIGS absorber is in the range from 3.5 μm down to 1.5 μm, the efficiency of the cell with a MoSe2 interfacial layer remains almost constant, about 24.6%, while that of the MoSe2-free solar cell decreases from 24.6% to 23.4%. Besides, a Schottky barrier height larger than 0.45 eV severely affects the fill factor and open circuit voltage of the solar cell with MoSe2 interface layer compared to the MoSe2-free solar cell.
本文的目的是分析界面MoSe2层对a /n-ZnO/i-ZnO/n-Zn(O,S)/p- cigs /p+-MoSe2/Mo/SLG太阳能电池性能的影响。在本研究中,使用数值模拟软件AFORS-HET计算了有和没有MoSe2层的电池的电特性。不同的实验工作都强调了在CIGS/Mo接触界面上存在薄膜MoSe2层。在隧穿效应下,该MoSe2层将肖特基CIGS/Mo接触性质转变为准欧姆性质。由于大量p掺杂,MoSe2薄层可以更好地将大多数载流子从CIGS隧穿到Mo。而且,MoSe2的带隙比CIGS吸收层的带隙更宽,从而在靠近背表面的地方产生电场。电场的存在减少了载流子在界面处的复合。在这些条件下,我们测试了有和没有MoSe2层的电池的性能。当吸收层厚度在3.5 ~ 1.5 μm范围内时,有MoSe2界面层的太阳能电池效率基本保持不变,约为24.6%,而无MoSe2界面层的太阳能电池效率从24.6%下降到23.4%。此外,当肖特基势垒高度大于0.45 eV时,有MoSe2界面层的太阳能电池的填充系数和开路电压都会受到较无MoSe2界面层的太阳能电池的影响。
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引用次数: 4
Generalized Power Akshaya Distribution and Its Applications 广义幂Akshaya分布及其应用
Pub Date : 2021-08-27 DOI: 10.4236/ojmsi.2021.94021
Ahmed T. Ramadan, A. Tolba, B. El-Desouky
In this paper, a new two-parameter distribution called generalized power Akshaya distribution extended from Akshaya distribution is introduced. This distribution is proposed to model lifetime data. Statistical properties like density, hazard, survival and moments are derived. Two parameters estimation is introduced using maximum likelihood and Bayesian techniques. Finally, an application of real data and a simulation study are introduced to illustrate the usefulness of the proposed distribution.
本文在Akshaya分布的基础上,引入了一种新的双参数分布,称为广义功率Akshaya分配。这种分布是为了对寿命数据进行建模而提出的。导出了密度、危险性、生存率和矩等统计特性。介绍了使用最大似然和贝叶斯技术进行双参数估计的方法。最后,介绍了实际数据的应用和模拟研究,以说明所提出的分布的有用性。
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引用次数: 10
Flexible Reduced Logarithmic-Inverse Lomax Distribution with Application for Bladder Cancer 柔性约对数逆Lomax分布在膀胱癌中的应用
Pub Date : 2021-08-27 DOI: 10.4236/ojmsi.2021.94023
M. M. Buzaridah, Dina A. Ramadan, B. El-Desouky
In this paper, a new method for adding parameters to a well-established distribution to obtain more flexible new families of distributions is applied to the inverse Lomax distribution (IFD). This method is known by the flexible reduced logarithmic-X family of distribution (FRL-X). The proposed distribution can be called a flexible reduced logarithmic-inverse Lomax distribution (FRL-IL). The statistical and reliability properties of the proposed models are studied including moments, order statistics, moment generating function, and quantile function. The estimation of the model parameters by maximum likelihood and the observed information matrix are also discussed. In order to assess the potential of the newly created distribution. The extended model is applied to real data and the results are given and compared to other models.
本文将一种新的方法应用于逆Lomax分布(IFD),该方法可以在已建立的分布中增加参数以获得更灵活的新分布族。这种方法被称为柔性简化对数- x分布族(FRL-X)。所提出的分布可称为柔性简化对数逆洛max分布(FRL-IL)。研究了模型的统计特性和可靠性,包括矩量、阶统计量、矩生成函数和分位数函数。讨论了用极大似然法和观测信息矩阵估计模型参数的方法。以评估新创建的分布的潜力。将该扩展模型应用于实际数据,并与其他模型进行了比较。
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引用次数: 3
A Sequential Shrinkage Estimating Method for Tobit Regression Model Tobit回归模型的序贯收缩估计方法
Pub Date : 2021-05-21 DOI: 10.4236/ojmsi.2021.93018
H. Lu, Cuiling Dong, Juling Zhou
In the applications of Tobit regression models we always encounter the data sets which contain too many variables that only a few of them contribute to the model. Therefore, it will waste much more samples to estimate the “non-effective” variables in the inference. In this paper, we use a sequential procedure for constructing the fixed size confidence set for the “effective” parameters to the model by using an adaptive shrinkage estimate such that the “effective” coefficients can be efficiently identified with the minimum sample size based on Tobit regression model. Fixed design is considered for numerical simulation.
在Tobit回归模型的应用中,我们经常遇到包含太多变量的数据集,其中只有少数变量对模型有贡献。因此,它会浪费更多的样本来估计推理中的“无效”变量。在本文中,我们使用一个顺序过程,通过自适应收缩估计来构造模型的“有效”参数的固定大小的置信集,使得“有效”系数可以有效地识别出基于Tobit回归模型的最小样本量。数值模拟采用固定设计。
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引用次数: 0
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