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An Outlier Detection Approach to Recognize the Sources of a Process Failure within a Multivariate Poisson Process 在多变量泊松过程中识别过程故障源的离群值检测方法
IF 2.4 3区 数学 Q1 MATHEMATICS Pub Date : 2024-09-11 DOI: 10.3390/math12182813
Chia-Ding Hou, Rung-Hung Su
Among attribute processes, the number of nonconformities conforming to a Poisson distribution is among the most crucial quality attributes. Furthermore, owing to the variety of quality attributes, the significance of the multivariate Poisson process in industry cannot be overstated. An out-of-control multivariate Poisson process can be detected using an alarm on a multivariate control chart. Nevertheless, pinpointing the specific quality attributes that led to the process shifts is complex. The study focuses on the causes that lead to process shifts in multivariate Poisson processes, unlike the majority of studies examining shifts in multivariate normal processes. This paper initially presents a statistical method for detecting outliers in a multivariate Poisson distribution. Furthermore, a progressive testing algorithm is then developed to identify the variables responsible for a failure within a multivariate Poisson process. According to simulation results, the proposed approach can effectively determine the sources of a process fault within a multivariate Poisson process.
在属性过程中,符合泊松分布的不合格数量是最关键的质量属性之一。此外,由于质量属性的多样性,多元泊松过程在工业中的重要性怎么强调都不为过。失控的多元泊松过程可以通过多元控制图上的警报来检测。然而,确定导致过程转变的具体质量属性非常复杂。与大多数研究多变量正态过程偏移的研究不同,本研究重点关注导致多变量泊松过程偏移的原因。本文首先介绍了一种在多元泊松分布中检测异常值的统计方法。此外,本文还开发了一种渐进测试算法,以确定在多元泊松过程中造成故障的变量。根据模拟结果,所提出的方法能有效确定多元泊松过程中的过程故障源。
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引用次数: 0
Some Equations in Rings Involving Semiprime Ideals and Multiplicative Generalized Semiderivations 环中涉及半等式和乘法广义半等式的一些方程
IF 2.4 3区 数学 Q1 MATHEMATICS Pub Date : 2024-09-11 DOI: 10.3390/math12182818
Ali Yahya Hummdi, Öznur Gölbaşı, Emine Koç Sögütcü, Nadeem ur Rehman
This paper examines the commutativity of the quotient ring F/Y by utilizing specific differential identities in a general ring F that contains a semiprime ideal Y. This study particularly focuses on the role of a multiplicative generalized semiderivation ψ, which is associated with a map θ, in determining the commutative nature of the quotient ring.
本文利用包含一个半质理想 Y 的一般环 F 中的特定微分等式,研究了商环 F/Y 的交换性。本研究特别关注与映射 θ 相关联的乘法广义半矢量 ψ 在确定商环的交换性中的作用。
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引用次数: 0
Singularity, Observability, and Independence: Unveiling Lorenz’s Cryptographic Potential 奇异性、可观测性和独立性:揭示洛伦兹的密码学潜力
IF 2.4 3区 数学 Q1 MATHEMATICS Pub Date : 2024-09-10 DOI: 10.3390/math12182798
Alexandru Dinu
The key findings of this study include a detailed examination of the Lorenz system’s observability, revealing that it maintains high observability compared to other chaotic systems, thus supporting its potential use in cryptographic applications. We also investigated the singularity manifolds, identifying regions where observability might be compromised, but overall demonstrating that the system remains reliable across various states. Additionally, statistical tests confirm that the Lorenz system exhibits strong statistical independence in its outputs, further validating its suitability for encryption purposes. These findings collectively underscore the Lorenz system’s potential to enhance cryptographic security and contribute significantly to the field of secure communications. By providing a thorough analysis of its key properties, this study positions the Lorenz system as a promising candidate for advanced encryption technologies.
本研究的主要发现包括对洛伦兹系统可观测性的详细研究,结果表明,与其他混沌系统相比,洛伦兹系统保持了较高的可观测性,因此支持其在密码学应用中的潜在用途。我们还研究了奇异性流形,确定了可观测性可能受到影响的区域,但总体上表明该系统在各种状态下都能保持可靠。此外,统计测试证实,洛伦兹系统的输出具有很强的统计独立性,这进一步验证了它在加密方面的适用性。这些发现共同强调了洛伦兹系统在提高密码安全性方面的潜力,并为安全通信领域做出了重大贡献。本研究通过对洛伦兹系统关键特性的全面分析,将其定位为先进加密技术的理想候选方案。
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引用次数: 0
A Novel Hybrid Model (EMD-TI-LSTM) for Enhanced Financial Forecasting with Machine Learning 利用机器学习增强金融预测的新型混合模型(EMD-TI-LSTM)
IF 2.4 3区 数学 Q1 MATHEMATICS Pub Date : 2024-09-09 DOI: 10.3390/math12172794
Olcay Ozupek, Reyat Yilmaz, Bita Ghasemkhani, Derya Birant, Recep Alp Kut
Financial forecasting involves predicting the future financial states and performance of companies and investors. Recent technological advancements have demonstrated that machine learning-based models can outperform traditional financial forecasting techniques. In particular, hybrid approaches that integrate diverse methods to leverage their strengths have yielded superior results in financial prediction. This study introduces a novel hybrid model, entitled EMD-TI-LSTM, consisting of empirical mode decomposition (EMD), technical indicators (TI), and long short-term memory (LSTM). The proposed model delivered more accurate predictions than those generated by the conventional LSTM approach on the same well-known financial datasets, achieving average enhancements of 39.56%, 36.86%, and 39.90% based on the MAPE, RMSE, and MAE metrics, respectively. Furthermore, the results show that the proposed model has a lower average MAPE rate of 42.91% compared to its state-of-the-art counterparts. These findings highlight the potential of hybrid models and mathematical innovations to advance the field of financial forecasting.
财务预测涉及对公司和投资者未来财务状况和业绩的预测。最近的技术进步表明,基于机器学习的模型可以超越传统的财务预测技术。特别是,融合多种方法以发挥其优势的混合方法在金融预测方面取得了卓越的成果。本研究介绍了一种名为 EMD-TI-LSTM 的新型混合模型,该模型由经验模式分解(EMD)、技术指标(TI)和长短期记忆(LSTM)组成。基于 MAPE、RMSE 和 MAE 指标,在相同的知名金融数据集上,所提出的模型比传统 LSTM 方法生成的预测结果更准确,平均提升率分别为 39.56%、36.86% 和 39.90%。此外,结果表明,与最先进的模型相比,拟议模型的平均 MAPE 率更低,为 42.91%。这些发现凸显了混合模型和数学创新在推动金融预测领域发展方面的潜力。
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引用次数: 0
Prediction of Wind Turbine Gearbox Oil Temperature Based on Stochastic Differential Equation Modeling 基于随机微分方程建模的风力涡轮机齿轮箱油温预测
IF 2.4 3区 数学 Q1 MATHEMATICS Pub Date : 2024-09-09 DOI: 10.3390/math12172783
Hongsheng Su, Zonghao Ding, Xingsheng Wang
Aiming at the problem of high failure rate and inconvenient maintenance of wind turbine gearboxes, this paper establishes a stochastic differential equation model that can be used to fit the change of gearbox oil temperature and adopts an iterative computational method and Markov-based modified optimization to fit the prediction sequence in order to realize the accurate prediction of gearbox oil temperature. The model divides the oil temperature change of the gearbox into two parts, internal aging and external random perturbation, adopts the approximation theorem to establish the internal aging model, and uses Brownian motion to simulate the external random perturbation. The model parameters were calculated by the Newton–Raphson iterative method based on the gearbox oil temperature monitoring data. Iterative calculations and Markov-based corrections were performed on the model prediction data. The gearbox oil temperature variations were simulated in MATLAB, and the fitting and testing errors were calculated before and after the iterations. By comparing the fitting and testing errors with the ordinary differential equations and the stochastic differential equations before iteration, the iterated model can better reflect the gear oil temperature trend and predict the oil temperature at a specific time. The accuracy of the iterated model in terms of fitting and prediction is important for the development of preventive maintenance.
针对风电齿轮箱故障率高、维护不便的问题,本文建立了可用于拟合齿轮箱油温变化的随机微分方程模型,并采用迭代计算方法和基于马尔可夫的修正优化来拟合预测序列,以实现对齿轮箱油温的精确预测。该模型将变速箱油温变化分为内部老化和外部随机扰动两部分,采用近似定理建立内部老化模型,利用布朗运动模拟外部随机扰动。根据变速箱油温监测数据,采用牛顿-拉夫逊迭代法计算模型参数。对模型预测数据进行了迭代计算和基于马尔可夫的修正。在 MATLAB 中模拟了变速箱油温的变化,并计算了迭代前后的拟合误差和测试误差。通过比较迭代前与常微分方程和随机微分方程的拟合误差和测试误差,迭代后的模型能更好地反映齿轮油温度的变化趋势,并预测特定时间的油温。迭代模型在拟合和预测方面的准确性对预防性维护的发展非常重要。
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引用次数: 0
Some Fractional Integral and Derivative Formulas Revisited 一些分式积分和导数公式再探讨
IF 2.4 3区 数学 Q1 MATHEMATICS Pub Date : 2024-09-09 DOI: 10.3390/math12172786
Juan Luis González-Santander, Francesco Mainardi
In the most common literature about fractional calculus, we find that Dtαaft=It−αaft is assumed implicitly in the tables of fractional integrals and derivatives. However, this is not straightforward from the definitions of Itαaft and Dtαaft. In this sense, we prove that Dt0ft=It−α0ft is true for ft=tν−1logt, and ft=eλt, despite the fact that these derivations are highly non-trivial. Moreover, the corresponding formulas for Dtα−∞t−δ and Itα−∞t−δ found in the literature are incorrect; thus, we derive the correct ones, proving in turn that Dtα−∞t−δ=It−α−∞t−δ holds true.
在有关分数微积分的最常见文献中,我们发现 Dtαaft=It-αaft 是分数积分和导数表中的隐含假设。然而,这与 Itαaft 和 Dtαaft 的定义并不直接相关。从这个意义上说,我们证明在 ft=tν-1logt 和 ft=eλt 时,Dt0ft=It-α0ft 为真,尽管这些推导非常不简单。此外,文献中发现的 Dtα-∞t-δ 和 Itα-∞t-δ 的相应公式是不正确的;因此,我们推导出正确的公式,进而证明 Dtα-∞t-δ=It-α-∞t-δ 成立。
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引用次数: 0
Quantitative and Qualitative Analysis of Aircraft Round-Trip Times Using Phase Type Distributions 利用相位类型分布对飞机往返时间进行定量和定性分析
IF 2.4 3区 数学 Q1 MATHEMATICS Pub Date : 2024-09-09 DOI: 10.3390/math12172795
Srinivas R. Chakravarthy
One of the major issues facing commercial airlines is the time that it takes to board passengers. Further, most airlines wish to increase the number of trips that an aircraft can make between two or more cities. Thus, reducing the overall boarding times by a few minutes will have a significant impact on the number of trips made by an aircraft, as well as enabling improvements in key measures such as the median and 75th and 95th percentiles. Looking at such measures other than the mean is critical as it is well known that the mean can under- or overestimate the performance of any model. While there is considerable literature on the study of strategies to decrease boarding times, the same cannot be said about the study of the boarding time given a particular strategy for boarding. Thus, the focus of this paper is to study analytically (using suitable stochastic models) and numerically the impact of reducing the average time on the key measures to help the system to plan accordingly. This is achieved using a well-known probability distribution, namely the phase type distribution, to model various events involved in the boarding process. Illustrative numerical results show a reduction in the percentile values when the average boarding times are decreased. Understanding the percentiles of the boarding times, as opposed to relying only on the average boarding times, will help management to adopt a better boarding strategy that in turn will lead to an increase in the number of trips that an aircraft can make.
商业航空公司面临的主要问题之一是乘客登机所需的时间。此外,大多数航空公司都希望增加飞机在两个或更多城市之间的飞行次数。因此,将整体登机时间缩短几分钟将对飞机的飞行次数产生重大影响,并能改善中位数、第 75 和第 95 百分位数等关键指标。众所周知,平均值可能会低估或高估任何模型的性能,因此,除平均值外,研究这些指标也至关重要。虽然有大量文献研究了减少登机时间的策略,但在研究特定登机策略下的登机时间时,情况却并非如此。因此,本文的重点是分析(使用合适的随机模型)和数值研究缩短平均时间对关键指标的影响,以帮助系统制定相应的计划。为此,我们采用了一种著名的概率分布,即相型分布,来模拟登机过程中涉及的各种事件。示例性数值结果显示,当平均登机时间缩短时,百分位数值也会降低。与仅依赖平均登机时间相比,了解登机时间的百分位数将有助于管理层采取更好的登机策略,进而增加飞机的飞行架次。
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引用次数: 0
Coarse-Gridded Simulation of the Nonlinear Schrödinger Equation with Machine Learning 利用机器学习对非线性薛定谔方程进行粗网格模拟
IF 2.4 3区 数学 Q1 MATHEMATICS Pub Date : 2024-09-09 DOI: 10.3390/math12172784
Benjamin F. Akers, Kristina O. F. Williams
A numerical method for evolving the nonlinear Schrödinger equation on a coarse spatial grid is developed. This trains a neural network to generate the optimal stencil weights to discretize the second derivative of solutions to the nonlinear Schrödinger equation. The neural network is embedded in a symmetric matrix to control the scheme’s eigenvalues, ensuring stability. The machine-learned method can outperform both its parent finite difference method and a Fourier spectral method. The trained scheme has the same asymptotic operation cost as its parent finite difference method after training. Unlike traditional methods, the performance depends on how close the initial data are to the training set.
本研究开发了一种在粗空间网格上演化非线性薛定谔方程的数值方法。该方法训练神经网络生成最佳模版权重,以离散化非线性薛定谔方程解的二次导数。神经网络被嵌入到一个对称矩阵中,以控制该方案的特征值,从而确保稳定性。机器学习方法的性能优于其母有限差分法和傅立叶谱法。训练后的方案与其母有限差分法具有相同的渐近运算成本。与传统方法不同的是,其性能取决于初始数据与训练集的接近程度。
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引用次数: 0
A Novel Brillouin and Langevin Functions Dynamic Model for Two Conflicting Social Groups: Study of R&D Processes 两个冲突社会群体的新型布里渊和朗格文函数动态模型:研发过程研究
IF 2.4 3区 数学 Q1 MATHEMATICS Pub Date : 2024-09-09 DOI: 10.3390/math12172788
Ekaterina V. Orlova
We consider a two-group social conflict under the corporates’ research and development (R&D) business processes. Conflict participants are divided into two groups depending on their attitude to new ideas, technologies, and behavioral style for R&D creative problems—innovators and adapters. We reveal the contradiction that arises between the need to include both types of employees in one project team and their objectively antagonistic positions regarding the methods and approaches to R&D processes. The proposed research methodology is based on a modern post-non-classical paradigm formed on the principles of coherence, interdisciplinarity, openness, and nonlinearity, as well as a sociophysical approach to the social conflicts modeling. We use the general theories of magnetism, paramagnetism, and functions of P. Langevin and L. Brillouin to describe the dynamics of group participants’ preferences regarding the style of conflict behavior. The analogy of paramagnetism, consisting in the orienting effect of the magnetic field, is used to describe social groups interactions that have not only their own interests, but are also influenced by the opinions of opposite social groups. A two-dimensional, four-parameter map represents the dynamics of group conflict. Modeling results show that regardless of the initial states and with certain parameters of intra-group and intergroup interactions, the trajectories eventually converge to an attractor (limit cycle) in a two-dimensional space. No non-periodic or chaotic modes are identified in the two-group conflict, which determines the controllability of the described conflict. The results of the simulation experiments are used as decision support and contradictions resolution aimed at forming the required modes of the corporates’ research and development business processes and ensuring the group participants’ cohesion and depolarization. The results of testing the model at an industrial enterprise are presented.
我们考虑了企业研发(R&D)业务流程下的两组社会冲突。冲突参与者根据其对新想法、新技术的态度以及对研发创造性问题的行为方式被分为两组--创新者和适应者。我们揭示了将这两类员工纳入一个项目团队的必要性与他们在研发流程的方法和途径方面的客观对立立场之间的矛盾。我们提出的研究方法是基于一种现代的后非经典范式,这种范式是在一致性、跨学科性、开放性和非线性原则以及社会冲突建模的社会物理学方法的基础上形成的。我们使用 P. 朗热文和 L. 布里卢安的磁学、准磁学和函数的一般理论来描述群体参与者对冲突行为方式的偏好动态。准磁学的类比,包括磁场的定向效应,被用来描述社会群体的互动,这些群体不仅有自己的利益,而且还受到相反社会群体意见的影响。一个二维四参数图代表了群体冲突的动态。建模结果表明,无论初始状态如何,只要有一定的群体内和群体间互动参数,轨迹最终都会收敛到二维空间中的吸引子(极限循环)。在两组冲突中没有发现非周期性或混乱模式,这就决定了所述冲突的可控性。模拟实验的结果被用作决策支持和矛盾解决,旨在形成企业研发业务流程所需的模式,确保群体参与者的凝聚力和去极化。本文介绍了该模型在一家工业企业的测试结果。
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引用次数: 0
Few-Shot Learning Sensitive Recognition Method Based on Prototypical Network 基于原型网络的少量学习敏感识别方法
IF 2.4 3区 数学 Q1 MATHEMATICS Pub Date : 2024-09-09 DOI: 10.3390/math12172791
Guoquan Yuan, Xinjian Zhao, Liu Li, Song Zhang, Shanming Wei
Traditional machine learning-based entity extraction methods rely heavily on feature engineering by experts, and the generalization ability of the model is poor. Prototype networks, on the other hand, can effectively use a small amount of labeled data to train models while using category prototypes to enhance the generalization ability of the models. Therefore, this paper proposes a prototype network-based named entity recognition (NER) method, namely the FSPN-NER model, to solve the problem of difficult recognition of sensitive data in data-sparse text. The model utilizes the positional coding model (PCM) to pre-train the data and perform feature extraction, then computes the prototype vectors to achieve entity matching, and finally introduces a boundary detection module to enhance the performance of the prototype network in the named entity recognition task. The model in this paper is compared with LSTM, BiLSTM, CRF, Transformer and their combination models, and the experimental results on the test dataset show that the model outperforms the comparative models with an accuracy of 84.8%, a recall of 85.8% and an F1 value of 0.853.
传统的基于机器学习的实体提取方法严重依赖专家的特征工程,模型的泛化能力较差。而原型网络可以有效地利用少量标注数据来训练模型,同时利用类别原型来增强模型的泛化能力。因此,本文提出了一种基于原型网络的命名实体识别(NER)方法,即 FSPN-NER 模型,以解决数据稀疏文本中敏感数据识别困难的问题。该模型利用位置编码模型(PCM)对数据进行预训练并进行特征提取,然后计算原型向量以实现实体匹配,最后引入边界检测模块以提高原型网络在命名实体识别任务中的性能。本文中的模型与 LSTM、BiLSTM、CRF、Transformer 及其组合模型进行了比较,在测试数据集上的实验结果表明,该模型的准确率为 84.8%,召回率为 85.8%,F1 值为 0.853,优于比较模型。
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引用次数: 0
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