Applied Stochastic Models in Business and Industry最新文献_第6页

Renewable Energy Investments, Support Schemes and the Dirty Option 可再生能源投资，支持计划和肮脏的选择

IF 1.3 4区数学

Applied Stochastic Models in Business and Industry Pub Date : 2024-10-26 DOI: 10.1002/asmb.2901

Domenico De Giovanni, Elena Iakimova

引用次数: 0

Simulated Exact Confidence Intervals: With Applications to Censored Exponential Reliability Data 模拟精确置信区间：与应用审查指数可靠性数据

IF 1.3 4区数学

Applied Stochastic Models in Business and Industry Pub Date : 2024-10-26 DOI: 10.1002/asmb.2900

Bo Henry Lindqvist, Gunnar Taraldsen

引用次数: 0

Bayesian Sequential Learning and Decision Making in Bike-Sharing Systems 共享单车系统中的贝叶斯顺序学习与决策

IF 1.3 4区数学

Applied Stochastic Models in Business and Industry Pub Date : 2024-10-23 DOI: 10.1002/asmb.2888

Tevfik Aktekin, Bumsoo Kim, Luis J. Novoa, Babak Zafari

引用次数: 0

Model Averaging for Estimating Treatment Effects With Binary Responses 用二元响应估计治疗效果的模型平均

IF 1.3 4区数学

Applied Stochastic Models in Business and Industry Pub Date : 2024-10-21 DOI: 10.1002/asmb.2898

Guangyuan Cui, Na Li, Alan T. K. Wan, Xinyu Zhang

引用次数: 0

A Methodological Approach to Prioritize Digital Twin Development in Manufacturing 制造业中数字孪生优先发展的方法论方法

IF 1.3 4区数学

Applied Stochastic Models in Business and Industry Pub Date : 2024-10-21 DOI: 10.1002/asmb.2889

Sara Blasco Román, Till Böttjer

{"title":"A Methodological Approach to Prioritize Digital Twin Development in Manufacturing","authors":"Sara Blasco Román, Till Böttjer","doi":"10.1002/asmb.2889","DOIUrl":"https://doi.org/10.1002/asmb.2889","url":null,"abstract":"<p>The digital age has brought about a need for organizations to utilize Digital Twins to improve operational efficiency and decision-making. However, it is difficult for companies to identify and prioritize Digital Twin initiatives that meet the needs of their stakeholders and align with the capabilities of the company and its strategic plans. This paper proposes a methodology for the systematic identification and prioritization of Digital Twin applications in complex industrial settings. The methodology begins by documenting business requirements, current processes, and challenges, and subsequently identifying areas with potential benefits from Digital Twins through the use of an opportunity scoring system. To refine the portfolio of Digital Twin applications to include only those that are impactful and viable, the feasibility of Digital Twin is quantified by evaluating technological (technical capacity and digital skills), organizational, and project risk factors. To validate the proposed methodology, a case study was conducted in collaboration with an industrial partner specializing in injection molding. This real-world application demonstrates the effectiveness of our approach in identifying and prioritizing Digital Twin applications in a complex industrial context. This research contributes to the growing body of knowledge surrounding Digital Twins, providing organizations with a structured approach to leverage the potential of this transformative technology.</p>","PeriodicalId":55495,"journal":{"name":"Applied Stochastic Models in Business and Industry","volume":"41 3","pages":""},"PeriodicalIF":1.3,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/asmb.2889","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144085165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Quantization-Based Latin Hypercube Sampling for Dependent Inputs With an Application to Sensitivity Analysis of Environmental Models 基于量化的依赖输入拉丁超立方采样及其在环境模型敏感性分析中的应用

IF 1.3 4区数学

Applied Stochastic Models in Business and Industry Pub Date : 2024-10-14 DOI: 10.1002/asmb.2899

Guerlain Lambert, Céline Helbert, Claire Lauvernet

{"title":"Quantization-Based Latin Hypercube Sampling for Dependent Inputs With an Application to Sensitivity Analysis of Environmental Models","authors":"Guerlain Lambert, Céline Helbert, Claire Lauvernet","doi":"10.1002/asmb.2899","DOIUrl":"https://doi.org/10.1002/asmb.2899","url":null,"abstract":"<p>Numerical models are essential for comprehending intricate physical phenomena in different domains. To handle their complexity, sensitivity analysis, particularly screening is crucial for identifying influential input parameters. Kernel-based methods, such as the Hilbert-Schmidt Independence Criterion (HSIC), are valuable for analyzing dependencies between inputs and outputs. Implementing HSIC requires data from the original model, which leads to the need of efficient sampling strategies to limit the number of costly numerical simulations. While, for independent input variables, existing sampling methods like Latin Hypercube Sampling (LHS) are effective in estimating HSIC with reduced variance, incorporating dependence is challenging. This article introduces a novel LHS variant, quantization-based LHS (QLHS), which leverages Voronoi vector quantization to address dependent inputs. The method provides good coverage of the range of variations in the input variables. The article outlines expectation estimators based on QLHS in various dependency settings, demonstrating their unbiasedness. The method is applied to several models of growing complexities, first on simple examples to illustrate the theory, then on more complex environmental hydrological models, when the dependence is known or not, and with more and more interactive processes and factors. The last application is on the digital twin of a French vineyard catchment (Beaujolais region) to design a vegetative filter strip and reduce water, sediment, and pesticide transfers from the fields to the river. QLHS is used to compute HSIC measures and independence tests, demonstrating its usefulness, especially in the context of complex models.</p>","PeriodicalId":55495,"journal":{"name":"Applied Stochastic Models in Business and Industry","volume":"41 3","pages":""},"PeriodicalIF":1.3,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/asmb.2899","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144085085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Model Bias Identification for Bayesian Calibration of Stochastic Digital Twins of Bridges 桥梁随机数字孪生贝叶斯校正的模型偏差辨识

IF 1.3 4区数学

Applied Stochastic Models in Business and Industry Pub Date : 2024-10-11 DOI: 10.1002/asmb.2897

Daniel Andrés Arcones, Martin Weiser, Phaedon-Stelios Koutsourelakis, Jörg F. Unger

{"title":"Model Bias Identification for Bayesian Calibration of Stochastic Digital Twins of Bridges","authors":"Daniel Andrés Arcones, Martin Weiser, Phaedon-Stelios Koutsourelakis, Jörg F. Unger","doi":"10.1002/asmb.2897","DOIUrl":"https://doi.org/10.1002/asmb.2897","url":null,"abstract":"<p>Simulation-based digital twins must provide accurate, robust, and reliable digital representations of their physical counterparts. Therefore, quantifying the uncertainty in their predictions plays a key role in making better-informed decisions that impact the actual system. The update of the simulation model based on data must then be carefully implemented. When applied to complex structures such as bridges, discrepancies between the computational model and the real system appear as model bias, which hinders the trustworthiness of the digital twin and increases its uncertainty. Classical Bayesian updating approaches aimed at inferring the model parameters often fail to compensate for such model bias, leading to overconfident and unreliable predictions. In this paper, two alternative model bias identification approaches are evaluated in the context of their applicability to digital twins of bridges. A modularized version of Kennedy and O'Hagan's approach and another one based on Orthogonal Gaussian Processes are compared with the classical Bayesian inference framework in a set of representative benchmarks. Additionally, two novel extensions are proposed for these models: the inclusion of noise-aware kernels and the introduction of additional variables not present in the computational model through the bias term. The integration of these approaches into the digital twin corrects the predictions, quantifies their uncertainty, estimates noise from unknown physical sources of error, and provides further insight into the system by including additional pre-existing information without modifying the computational model.</p>","PeriodicalId":55495,"journal":{"name":"Applied Stochastic Models in Business and Industry","volume":"41 3","pages":""},"PeriodicalIF":1.3,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/asmb.2897","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144085171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Framework for Cyber Risk Loss Distribution of Client-Server Networks: A Bond Percolation Model and Industry Specific Case Studies 客户端-服务器网络的网络风险损失分布框架：债券渗透模型和特定行业案例研究

IF 1.3 4区数学

Applied Stochastic Models in Business and Industry Pub Date : 2024-10-08 DOI: 10.1002/asmb.2896

Stefano Chiaradonna, Petar Jevtić, Nicolas Lanchier, Sasa Pesic

{"title":"Framework for Cyber Risk Loss Distribution of Client-Server Networks: A Bond Percolation Model and Industry Specific Case Studies","authors":"Stefano Chiaradonna, Petar Jevtić, Nicolas Lanchier, Sasa Pesic","doi":"10.1002/asmb.2896","DOIUrl":"https://doi.org/10.1002/asmb.2896","url":null,"abstract":"<div>\u0000 \u0000 <p>Cyber risk has emerged as a significant threat to businesses that have increasingly relied on new and existing information technologies (IT). Across various businesses in different industries and sectors, a distinct pattern of IT network architectures, such as the client-server network architecture, may, in principle, expose those businesses, which share it, to similar cyber risks. That is why in this article, we propose a probabilistic structural framework for loss assessments of cyber risks on the class of client-server network architectures with <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>K</mi>\u0000 </mrow>\u0000 <annotation>$$ K $$</annotation>\u0000 </semantics></math> different client types. To our knowledge, there exist no theoretical models of an aggregate loss distribution for cyber risk in this setting. With this structural framework via the exact mean and variance of losses, we demonstrate how the changing cybersecurity environment of a business's IT network impacts the loss distribution. Furthermore, our framework provides insights into better investment strategies for cybersecurity protection on the client-server network. Motivated by cyberattacks across industries, we apply our framework to four case studies that utilize the client-server network architecture. Our first application is implantable medical devices in healthcare. Our second application is the smart buildings domain. Third, we present an application for ride-sharing services such as Uber and Lyft. The fourth is the application of vehicle-to-vehicle cooperation in traffic management. The results are corresponding exact means and variances of cyber risk loss distributions parameterized by various cybersecurity parameters allowing for liability assessments and decisions in cybersecurity protection investments.</p>\u0000 </div>","PeriodicalId":55495,"journal":{"name":"Applied Stochastic Models in Business and Industry","volume":"40 6","pages":"1712-1733"},"PeriodicalIF":1.3,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142868212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Limiting Behavior of Mixed Coherent Systems With Lévy-Frailty Marshall–Olkin Failure Times 具有 Lévy-Frailty Marshall-Olkin 故障时间的混合相干系统的极限行为

IF 1.3 4区数学

Applied Stochastic Models in Business and Industry Pub Date : 2024-10-08 DOI: 10.1002/asmb.2893

Guido Lagos, Javiera Barrera, Pablo Romero, Juan Valencia

{"title":"Limiting Behavior of Mixed Coherent Systems With Lévy-Frailty Marshall–Olkin Failure Times","authors":"Guido Lagos, Javiera Barrera, Pablo Romero, Juan Valencia","doi":"10.1002/asmb.2893","DOIUrl":"https://doi.org/10.1002/asmb.2893","url":null,"abstract":"<div>\u0000 \u0000 <p>In this article, we show a limit result for the reliability function of a system—that is, the probability that the whole system is still operational after a certain given time—when the number of components of the system grows to infinity. More specifically, we consider a sequence of mixed coherent systems whose components are homogeneous and non-repairable, with failure-times governed by a Lévy-Frailty Marshall–Olkin (LFMO) distribution—a distribution that allows simultaneous component failures. We show that under integrability conditions the reliability function converges to the probability of a first-passage time of a Lévy subordinator process. To the best of our knowledge, this is the first result to tackle the asymptotic behavior of the reliability function as the number of components of the system grows. To illustrate our approach, we give an example of a parametric family of reliability functions where the system failure time converges in distribution to an exponential random variable, and give computational experiments testing convergence.</p>\u0000 </div>","PeriodicalId":55495,"journal":{"name":"Applied Stochastic Models in Business and Industry","volume":"40 5","pages":"1229-1244"},"PeriodicalIF":1.3,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142447659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Order Statistics Perspective for System Reliability 系统可靠性的顺序统计透视

IF 1.3 4区数学

Applied Stochastic Models in Business and Industry Pub Date : 2024-10-08 DOI: 10.1002/asmb.2895

Jingzhe Lei, Way Kuo

引用次数: 0