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Fault Monitoring Method for the Process Industry System Based on the Improved Dense Connection Network 基于改进型密集连接网络的流程工业系统故障监测方法
IF 2.4 3区 数学 Q1 MATHEMATICS Pub Date : 2024-09-13 DOI: 10.3390/math12182843
Jiarula Yasenjiang, Zhigang Lan, Kai Wang, Luhui Lv, Chao He, Yingjun Zhao, Wenhao Wang, Tian Gao
The safety of chemical processes is of critical importance. However, traditional fault monitoring methods have insufficiently studied the monitoring accuracy of multi-channel data and have not adequately considered the impact of noise on industrial processes. To address this issue, this paper proposes a neural network-based model, DSCBAM-DenseNet, which integrates depthwise separable convolution and attention modules to fuse multi-channel data features and enhance the model’s noise resistance. We simulated a real environment by adding Gaussian noise with different signal-to-noise ratios to the Tennessee Eastman process dataset and trained the model using multi-channel data. The experimental results show that this model outperforms traditional models in both fault diagnosis accuracy and noise resistance. Further research on a compressor unit engineering instance validated the superiority of the model.
化学过程的安全至关重要。然而,传统的故障监测方法对多通道数据的监测精度研究不足,也没有充分考虑噪声对工业过程的影响。针对这一问题,本文提出了一种基于神经网络的模型 DSCBAM-DenseNet,该模型集成了深度可分离卷积和注意力模块,可融合多通道数据特征并增强模型的抗噪能力。我们模拟了真实环境,在田纳西州伊士曼流程数据集中添加了不同信噪比的高斯噪声,并使用多通道数据对模型进行了训练。实验结果表明,该模型在故障诊断准确性和抗噪声能力方面均优于传统模型。对压缩机组工程实例的进一步研究验证了该模型的优越性。
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引用次数: 0
A Multi-Strategy Enhanced Hybrid Ant–Whale Algorithm and Its Applications in Machine Learning 多策略增强型混合蚁鲸算法及其在机器学习中的应用
IF 2.4 3区 数学 Q1 MATHEMATICS Pub Date : 2024-09-13 DOI: 10.3390/math12182848
Chenyang Gao, Yahua He , Yuelin Gao
Based on the principles of biomimicry, evolutionary algorithms (EAs) have been widely applied across diverse domains to tackle practical challenges. However, the inherent limitations of these algorithms call for further refinement to strike a delicate balance between global exploration and local exploitation. Thus, this paper introduces a novel multi-strategy enhanced hybrid algorithm called MHWACO, which integrates a Whale Optimization Algorithm (WOA) and Ant Colony Optimization (ACO). Initially, MHWACO employs Gaussian perturbation optimization for individual initialization. Subsequently, individuals selectively undertake either localized exploration based on the refined WOA or global prospecting anchored in the Golden Sine Algorithm (Golden-SA), determined by transition probabilities. Inspired by the collaborative behavior of ant colonies, a Flight Ant (FA) strategy is proposed to guide unoptimized individuals toward potential global optimal solutions. Finally, the Gaussian scatter search (GSS) strategy is activated during low population activity, striking a balance between global exploration and local exploitation capabilities. Moreover, the efficacy of Support Vector Regression (SVR) and random forest (RF) as regression models heavily depends on parameter selection. In response, we have devised the MHWACO-SVM and MHWACO-RF models to refine the selection of parameters, applying them to various real-world problems such as stock prediction, housing estimation, disease forecasting, fire prediction, and air quality monitoring. Experimental comparisons against 9 newly proposed intelligent optimization algorithms and 9 enhanced algorithms across 34 benchmark test functions and the CEC2022 benchmark suite, highlight the notable superiority and efficacy of MSWOA in addressing global optimization problems. Finally, the proposed MHWACO-SVM and MHWACO-RF models outperform other regression models across key metrics such as the Mean Bias Error (MBE), Coefficient of Determination (R2), Mean Absolute Error (MAE), Explained Variance Score (EVS), and Median Absolute Error (MEAE).
基于仿生学原理,进化算法(EAs)已被广泛应用于不同领域,以应对实际挑战。然而,这些算法的固有局限性要求进一步完善,以在全局探索和局部开发之间取得微妙的平衡。因此,本文介绍了一种名为 MHWACO 的新型多策略增强混合算法,它集成了鲸鱼优化算法(WOA)和蚁群优化算法(ACO)。最初,MHWACO 采用高斯扰动优化进行个体初始化。随后,个体选择性地进行基于精炼 WOA 的局部探索或基于黄金正弦算法(Golden-SA)的全局勘探,这由过渡概率决定。受蚂蚁群落协作行为的启发,我们提出了一种飞行蚂蚁(FA)策略,以引导未优化个体找到潜在的全局最优解。最后,高斯散点搜索(GSS)策略在种群活动较低时被激活,从而在全局探索和局部开发能力之间取得平衡。此外,支持向量回归(SVR)和随机森林(RF)作为回归模型的功效在很大程度上取决于参数选择。为此,我们设计了 MHWACO-SVM 和 MHWACO-RF 模型来改进参数选择,并将其应用于股票预测、住房估算、疾病预测、火灾预测和空气质量监测等各种实际问题。在 34 个基准测试函数和 CEC2022 基准套件中,MSWOA 与 9 种新提出的智能优化算法和 9 种增强算法进行了实验比较,凸显了 MSWOA 在解决全局优化问题方面的显著优势和功效。最后,在平均偏差 (MBE)、决定系数 (R2)、平均绝对误差 (MAE)、解释方差得分 (EVS) 和中位绝对误差 (MEAE) 等关键指标方面,拟议的 MHWACO-SVM 和 MHWACO-RF 模型优于其他回归模型。
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引用次数: 0
Applications of Generalized Hypergeometric Distribution on Comprehensive Families of Analytic Functions 广义超几何分布在分析函数综合族中的应用
IF 2.4 3区 数学 Q1 MATHEMATICS Pub Date : 2024-09-13 DOI: 10.3390/math12182851
Tariq Al-Hawary, Basem Frasin, Ibtisam Aldawish
A sequence of n trials from a finite population with no replacement is described by the hypergeometric distribution as the number of successes. Calculating the likelihood that factory-produced items would be defective is one of the most popular uses of the hypergeometric distribution in industrial quality control. Very recently, several researchers have applied this distribution on certain families of analytic functions. In this study, we provide certain adequate criteria for the generalized hypergeometric distribution series to be in two families of analytic functions defined in the open unit disk. Furthermore, we consider an integral operator for the hypergeometric distribution. Some corollaries will be implied from our main results.
超几何分布用成功次数来描述从有限群体中进行的 n 次无替换试验序列。计算工厂生产的产品出现缺陷的可能性是超几何分布在工业质量控制中最常用的方法之一。最近,一些研究人员将该分布应用于某些分析函数族。在本研究中,我们为广义超几何分布序列进入定义在开放单位盘中的两个解析函数族提供了某些适当的标准。此外,我们还考虑了超几何分布的积分算子。我们的主要结果将隐含一些推论。
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引用次数: 0
Discrete Random Renewable Replacements after the Expiration of Collaborative Preventive Maintenance Warranty 合作预防性维护保修期到期后的离散随机可再生更换
IF 2.4 3区 数学 Q1 MATHEMATICS Pub Date : 2024-09-13 DOI: 10.3390/math12182845
Hui Chen, Jie Chen, Yangyang Lai, Xiaoqi Yu, Lijun Shang, Rui Peng, Baoliang Liu
With advanced digital technologies as the key support, many scholars and researchers have proposed various random warranty models by integrating mission cycles into the warranty stage. However, these existing warranty models are designed only from the manufacturer’s subjective perspective, ignoring certain consumer requirements. For instance, they overlook a wide range of warranty coverage, the pursuit of reliability improvement rather than mere minimal repair, and the need to limit the delay in repair. To address these consumer requirements, this paper proposes a novel random collaborative preventive maintenance warranty with repair-time threshold (RCPMW-RTT). This model incorporates terms that are jointly designed by manufacturers and consumers to meet specific consumer needs, thereby overcoming the limitations of existing warranty models. The introduction of a repair-time threshold aims to limit the time delay in repairing failures and to compensate for any losses incurred by consumers. Using probability theory, the RCPMW-RTT is evaluated in terms of cost and time, and relevant variants are derived by analyzing key parameters. As an exemplary representation of the RCPMW-RTT, two random replacement policies named the discrete random renewable back replacement (DRRBR) and the discrete random renewable front replacement (DRRFR) are proposed and modelled to ensure reliability after the expiration of the RCPMW-RTT. In both policies, product replacement is triggered either by the occurrence of the first extreme mission cycle or by reaching the limit on the number of non-extreme mission cycles, whichever comes first. Probability theory is used to present cost rates for both policies in order to determine optimal values for decision variables. Finally, numerical analysis is performed on the RCPMW-RTT to reveal hidden variation tendencies and mechanisms; numerical analysis is also performed on the DRRBR and the DRRFR. The numerical results show that the proposed random replacement policies are feasible and unique; the replacement time within the post-warranty coverage increases as the maintenance quality improves and the cost rate can be reduced by setting a smaller repair-time threshold.
以先进的数字技术为重要支撑,许多学者和研究人员将任务周期融入保修阶段,提出了各种随机保修模式。然而,现有的这些保修模式仅从制造商的主观角度出发进行设计,忽视了消费者的某些需求。例如,它们忽视了保修范围的广泛性、追求可靠性的提高而不仅仅是最小维修量,以及限制维修延迟的需求。针对消费者的这些要求,本文提出了一种新颖的随机协同预防性维护保修与维修时间阈值(RCPMW-RTT)。该模式包含了由制造商和消费者共同设计的条款,以满足消费者的特定需求,从而克服了现有保修模式的局限性。引入维修时间阈值的目的是限制故障维修的时间延迟,并补偿消费者的任何损失。利用概率论,从成本和时间的角度对 RCPMW-RTT 进行了评估,并通过分析关键参数得出了相关变体。作为 RCPMW-RTT 的示例,提出并模拟了两种随机更换策略,即离散随机可再生后置更换 (DRRBR) 和离散随机可再生前置更换 (DRRFR),以确保 RCPMW-RTT 到期后的可靠性。在这两种策略中,产品替换都是在出现第一个极端任务周期或达到非极端任务周期数量限制时触发的,以先到者为准。概率论用于提出这两种政策的成本率,以确定决策变量的最佳值。最后,对 RCPMW-RTT 进行了数值分析,以揭示隐藏的变化趋势和机制;还对 DRRBR 和 DRRFR 进行了数值分析。数值结果表明,所提出的随机更换策略是可行的,也是唯一的;随着维护质量的提高,保修期后覆盖范围内的更换时间也会增加,而且通过设置较小的维修时间阈值可以降低成本率。
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引用次数: 0
Stability and Hopf Bifurcation Analysis of a Predator–Prey Model with Weak Allee Effect Delay and Competition Delay 具有弱阿利效应延迟和竞争延迟的捕食者-猎物模型的稳定性和霍普夫分岔分析
IF 2.4 3区 数学 Q1 MATHEMATICS Pub Date : 2024-09-13 DOI: 10.3390/math12182853
Yurong Dong, Hua Liu, Yumei Wei, Qibin Zhang, Gang Ma
The purpose of this paper is to study a predator–prey model with Allee effect and double time delays. This research examines the dynamics of the model, with a focus on positivity, existence, stability and Hopf bifurcations. The stability of the periodic solution and the direction of the Hopf bifurcation are elucidated by applying the normal form theory and the center manifold theorem. To validate the correctness of the theoretical analysis, numerical simulations were conducted. The results suggest that a weak Allee effect delay can promote stability within the model, transitioning it from instability to stability. Nevertheless, the competition delay induces periodic oscillations and chaotic dynamics, ultimately resulting in the population’s collapse.
本文旨在研究一个具有阿利效应和双重时间延迟的捕食者-猎物模型。本研究探讨了该模型的动力学,重点是正相关性、存在性、稳定性和霍普夫分岔。通过应用正态形式理论和中心流形定理,阐明了周期解的稳定性和霍普夫分岔的方向。为了验证理论分析的正确性,还进行了数值模拟。结果表明,弱阿利效应延迟能促进模型的稳定性,使其从不稳定性过渡到稳定性。然而,竞争延迟会引起周期性振荡和混乱动力学,最终导致种群崩溃。
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引用次数: 0
Third-Order Noncanonical Neutral Delay Differential Equations: Nonexistence of Kneser Solutions via Myshkis Type Criteria 三阶非正则中性延迟微分方程:通过 Myshkis 型准则的 Kneser 解决方案的不存在性
IF 2.4 3区 数学 Q1 MATHEMATICS Pub Date : 2024-09-13 DOI: 10.3390/math12182847
Gunasekaran Nithyakala, George E. Chatzarakis, Govindasamy Ayyappan, Ethiraju Thandapani
The purpose of this paper is to add some new asymptotic and oscillatory results for third-order neutral delay differential equations with noncanonical operators. Without assuming any extra conditions, by using the canonical transform technique, the studied equation is changed to a canonical type equation, and this reduces the number of classes of nonoscillatory solutions into two instead of four. Then, we obtain Myshkis type sufficient conditions for the nonexistence of Kneser type solutions for the studied equation. Finally, employing these newly obtained criteria, we provide conditions for the oscillation of all solutions of the studied equation. Examples are presented to illustrate the importance and the significance of the main results.
本文旨在为带有非规范算子的三阶中性延迟微分方程补充一些新的渐近和振荡结果。在不假定任何额外条件的情况下,通过使用典型变换技术,将所研究的方程变为典型类型方程,从而将非振荡解的类数从四类减少为两类。然后,我们得到了所研究方程不存在 Kneser 类型解的 Myshkis 型充分条件。最后,利用这些新获得的标准,我们为所研究方程的所有解的振荡提供了条件。我们将举例说明主要结果的重要性和意义。
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引用次数: 0
Efficient Study on Westervelt-Type Equations to Design Metamaterials via Symmetry Analysis 通过对称分析设计超材料的 Westervelt 型方程的高效研究
IF 2.4 3区 数学 Q1 MATHEMATICS Pub Date : 2024-09-13 DOI: 10.3390/math12182855
Zehra Pinar Izgi, Pshtiwan Othman Mohammed, Ravi P. Agarwal, Majeed A. Yousif, Alina Alb Lupas, Mohamed Abdelwahed
Abstract: Metamaterials have emerged as a focal point in contemporary science and technology due to their ability to drive significant innovations. These engineered materials are specifically designed to couple the phenomena of different physical natures, thereby influencing processes through mechanical or thermal effects. While much of the recent research has concentrated on frequency conversion into electromagnetic waves, the field of acoustic frequency conversion still faces considerable technical challenges. To overcome these hurdles, researchers are developing metamaterials with customized acoustic properties. A key equation for modeling nonlinear acoustic wave phenomena is the dissipative Westervelt equation. This study investigates analytical solutions using ansatz-based methods combined with Lie symmetries. The approach presented here provides a versatile framework that is applicable to a wide range of fields in metamaterial design.
摘要:超材料因其推动重大创新的能力而成为当代科学技术的焦点。这些工程材料经过专门设计,可将不同物理特性的现象耦合在一起,从而通过机械或热效应影响各种过程。虽然近期的大部分研究都集中在电磁波的频率转换上,但声频转换领域仍然面临着相当大的技术挑战。为了克服这些障碍,研究人员正在开发具有定制声学特性的超材料。非线性声波现象建模的一个关键方程是耗散 Westervelt 方程。本研究采用基于反演的方法,结合李氏对称性,研究分析解法。本文介绍的方法提供了一个通用框架,适用于超材料设计的广泛领域。
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引用次数: 0
A Particle Swarm Optimization-Based Interpretable Spiking Neural Classifier with Time-Varying Weights 基于粒子群优化的时变权重可解释尖峰神经分类器
IF 2.4 3区 数学 Q1 MATHEMATICS Pub Date : 2024-09-13 DOI: 10.3390/math12182846
Mohammed Thousif, Shirin Dora, Suresh Sundaram
This paper presents an interpretable, spiking neural classifier (IpT-SNC) with time-varying weights. IpT-SNC uses a two-layered spiking neural network (SNN) architecture in which weights of synapses are modeled using amplitude-modulated, time-varying Gaussian functions. Self-regulated particle swarm optimization (SRPSO) is used to update the amplitude, width, and centers of the Gaussian functions and thresholds of neurons in the output layer. IpT-SNC has been developed to improve the interpretability of spiking neural networks. The time-varying weights in IpT-SNC allow us to describe the rationale behind predictions in terms of specific input spikes. The performance of IpT-SNC is evaluated on ten benchmark datasets in the UCI machine learning repository and compared with the performance of other learning algorithms. According to the performance results, IpT-SNC enhances classification performance on testing datasets from a minimum of 0.5% to a maximum of 7.7%. The significance level of IpT-SNC with other learning algorithms is evaluated using statistical tests like the Friedman test and the paired t-test. Furthermore, on the challenging real-world BCI (Brain Computer Interface) competition IV dataset, IpT-SNC outperforms current classifiers by about 8% in terms of classification accuracy. The results indicate that IpT-SNC has better generalization performance than other algorithms.
本文介绍了一种具有时变权重的可解释尖峰神经分类器(IpT-SNC)。IpT-SNC 采用双层尖峰神经网络(SNN)架构,其中突触权重使用振幅调制的时变高斯函数建模。自调控粒子群优化(SRPSO)用于更新高斯函数的振幅、宽度和中心,以及输出层神经元的阈值。IpT-SNC 的开发是为了提高尖峰神经网络的可解释性。IpT-SNC 中的时变权重允许我们根据特定的输入尖峰来描述预测背后的原理。我们在 UCI 机器学习库中的十个基准数据集上评估了 IpT-SNC 的性能,并将其与其他学习算法的性能进行了比较。根据性能结果,IpT-SNC 提高了测试数据集的分类性能,最低为 0.5%,最高为 7.7%。通过弗里德曼检验和配对 t 检验等统计检验,评估了 IpT-SNC 与其他学习算法的显著性水平。此外,在具有挑战性的现实世界 BCI(脑机接口)竞赛 IV 数据集上,IpT-SNC 的分类准确率比现有分类器高出约 8%。结果表明,与其他算法相比,IpT-SNC 具有更好的泛化性能。
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引用次数: 0
A Novel Tourist Trip Design Problem with Stochastic Travel Times and Partial Charging for Battery Electric Vehicles 具有随机旅行时间和电池电动汽车部分充电功能的新型旅游行程设计问题
IF 2.4 3区 数学 Q1 MATHEMATICS Pub Date : 2024-09-11 DOI: 10.3390/math12182822
Samita Kedkaew, Warisa Nakkiew, Parida Jewpanya, Wasawat Nakkiew
This study proposes a novel mathematical model for the Multi-Day Tourist Trip Design Problem with Stochastic Travel Time and Partial Charging for Battery Electric Vehicle (MD-TTDP-STT-PCBEV). To the best of our knowledge, no prior study has fully incorporated the use of BEVs into TTDP models. Given the limited driving range of BEVs, the model requires decisions regarding the locations and policy for recharging the vehicle’s battery. The problem also incorporates real-world uncertainty by considering travel time as a random variable subjected to normal distribution. The model is formulated using chance-constraint programming, aiming to find optimal tourist routes for BEVs that maximize tourist satisfaction. Numerical experiments were conducted to compare solutions between stochastic and deterministic environments. Computational experiments using the LINGO optimization solver demonstrated that the total rating scores obtained from the stochastic model with chance-constraint programming were generally lower than those from the deterministic model due to travel time uncertainties. These results highlight the importance of incorporating real-world uncertainty and variability to achieve more accurate and reliable planning.
本研究针对具有随机旅行时间和电池电动汽车部分充电的多日旅游行程设计问题(MD-TTDP-STT-PCBEV)提出了一个新颖的数学模型。据我们所知,此前还没有任何研究将电动汽车的使用完全纳入 TTDP 模型。鉴于 BEV 的行驶里程有限,该模型需要对车辆电池充电的地点和政策做出决策。通过将旅行时间视为服从正态分布的随机变量,该问题还纳入了现实世界的不确定性。该模型采用机会约束程序设计法,旨在为 BEV 找到游客满意度最大化的最佳旅游路线。通过数值实验比较了随机环境和确定性环境下的解决方案。使用 LINGO 优化求解器进行的计算实验表明,由于旅行时间的不确定性,采用机会约束编程的随机模型得到的总评分通常低于确定性模型得到的评分。这些结果凸显了将现实世界的不确定性和可变性纳入规划以实现更准确、更可靠规划的重要性。
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引用次数: 0
Rigid Polynomial Differential Systems with Homogeneous Nonlinearities 具有同质非线性的刚性多项式微分系统
IF 2.4 3区 数学 Q1 MATHEMATICS Pub Date : 2024-09-11 DOI: 10.3390/math12182806
Jaume Llibre
Planar differential systems whose angular velocity is constant are called rigid or uniform differential systems. The first rigid system goes back to the pendulum clock of Christiaan Huygens in 1656; since then, the interest for the rigid systems has been growing. Thus, at this moment, in MathSciNet there are 108 articles with the words rigid systems or uniform systems in their titles. Here, we study the dynamics of the planar rigid polynomial differential systems with homogeneous nonlinearities of arbitrary degree. More precisely, we characterize the existence and non-existence of limit cycles in this class of rigid systems, and we determine the local phase portraits of their finite and infinite equilibrium points in the Poincaré disc. Finally, we classify the global phase portraits in the Poincaré disc of the rigid polynomial differential systems of degree two, and of one class of rigid polynomial differential systems with cubic homogeneous nonlinearities that can exhibit one limit cycle.
角速度恒定的平面微分系统被称为刚性或均匀微分系统。第一个刚性系统可追溯到 1656 年克里斯蒂安-惠更斯(Christiaan Huygens)的摆钟;从那时起,人们对刚性系统的兴趣与日俱增。因此,目前在 MathSciNet 上有 108 篇文章的标题带有刚性系统或均匀系统的字样。在此,我们研究具有任意度同质非线性的平面刚性多项式微分系统的动力学。更确切地说,我们描述了这一类刚性系统中极限循环的存在和不存在,并确定了它们在波恩卡莱圆盘中有限和无限平衡点的局部相位肖像。最后,我们对二度刚性多项式微分方程系统和一类具有立方均质非线性的刚性多项式微分方程系统在 Poincaré 圆盘中的全局相位肖像进行了分类,这些系统可以表现出一个极限循环。
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引用次数: 0
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