Transportation Research Part E-Logistics and Transportation Review最新文献_第2页

Optimizing first-and-last-mile ridesharing services with a heterogeneous vehicle fleet and time-dependent travel times 优化具有异构车队和随时间变化的出行时间的首末英里共享乘车服务

IF 8.3 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2024-11-11 DOI: 10.1016/j.tre.2024.103847

Bo Sun , Shukai Chen , Qiang Meng

This study investigates an on-demand first-and-last-mile ridesharing service (FLRS) problem considering the time-dependent travel time for an operator who manage a heterogeneous vehicle fleet. The operator, aiming to minimize the total operational cost, needs to simultaneously serve both first-mile (FM) and last-mile (LM) trips around a public transportation hub, such as a metro station. To holistically address this problem, we formulate a time-discretized mixed integer linear programming (MILP) model by constructing a time-expanded network and then extend a route-based set partitioning model. To yield good-quality solutions in a short computational time, a rolling-horizon-based column generation (RHCG) method is developed to handle real-time requests. An exact branch-and-price (BP) algorithm and a customized adaptive large neighborhood search (ALNS) algorithm are utilized to assess the solution quality of the applied RHCG. We conduct extensive numerical experiments created from real-world instances in Singapore to demonstrate the effectiveness of the proposed research methodology. The results of large-scale cases indicate that the RHCG outperforms both the commercial solver and the BP, and significantly reduces computational time in comparison with the ALNS. The implemented FLRS solution can decrease system-wide costs by 21.38% and increase shared-ride efficiency by 1.47 times, compared with the FM and LM services that operate separately.

本研究探讨了一个按需提供的 "第一英里和最后一英里 "共享乘车服务（FLRS）问题，该问题考虑到了管理异构车队的运营商随时间变化的旅行时间。运营商的目标是最大限度地降低总运营成本，需要同时为地铁站等公共交通枢纽周围的 "最初一英里"（FM）和 "最后一英里"（LM）行程提供服务。为了从整体上解决这一问题，我们通过构建一个时间扩展网络来建立一个时间具体化的混合整数线性规划（MILP）模型，然后扩展一个基于路线集划分的模型。为了在较短的计算时间内获得高质量的解决方案，我们开发了一种基于滚动远景的列生成（RHCG）方法来处理实时请求。我们利用精确的分支定价（BP）算法和定制的自适应大邻域搜索（ALNS）算法来评估应用 RHCG 的解质量。我们根据新加坡的实际情况进行了大量数值实验，以证明所提研究方法的有效性。大规模案例的结果表明，与 ALNS 相比，RHCG 优于商业求解器和 BP，并显著减少了计算时间。与单独运行的 FM 和 LM 服务相比，实施的 FLRS 解决方案可将整个系统的成本降低 21.38%，将共享乘车效率提高 1.47 倍。

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引用次数: 0

Mobile COVID-19 vaccination scheduling with capacity selection 移动 COVID-19 疫苗接种调度与容量选择

IF 8.3 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2024-11-11 DOI: 10.1016/j.tre.2024.103826

Lianhua Tang , Yantong Li , Shuai Zhang , Zheng Wang , Leandro C. Coelho

Massive COVID-19 vaccination can significantly reduce both mild and severe infection rates. Some governments have adopted mobile vaccination vehicles, offering a more convenient and flexible service compared to static walk-in sites. This paper addresses a new scheduling problem arising from the mobile COVID-19 vaccination planning practice. Given a set of communities, each with a specific number of residents to vaccinate, the objective is to assign mobile vaccination vehicles to communities and determine each vehicle’s service capacity and routes, attempting to minimize the total operational cost. To our knowledge, this is the first attempt to tackle the joint challenge of mass vaccination scheduling and routing. We formulate the problem as a mixed-integer nonlinear program model, which we linearize by treating each vehicle with multiple stations as separate units. Given that the problem is NP-hard, we then developed a tailored adaptive large neighborhood search (ALNS) approach that effectively solves practical-sized instances by utilizing the intrinsic structure of the problem. To illustrate the efficiency of the suggested model and solution methodologies, we conduct numerical experiments on instances of varying sizes. The results demonstrate the effectiveness of the developed ALNS algorithm in solving instances with realistic sizes, efficiently handling up to 100 communities and 14 vaccination vehicles. In addition, a case study shows that our method significantly reduces operational expenses compared to some experience-based greedy methods.

大规模接种 COVID-19 可大大降低轻度和重度感染率。与固定的步行接种点相比，一些政府采用了流动接种车，提供更方便、更灵活的服务。本文探讨了流动 COVID-19 疫苗接种规划实践中出现的新调度问题。给定一组社区（每个社区都有特定数量的居民需要接种疫苗），目标是将流动疫苗接种车辆分配到各社区，并确定每辆车的服务能力和路线，力图使总运营成本最小化。据我们所知，这是首次尝试解决大规模疫苗接种调度和路线选择的联合挑战。我们将这一问题表述为一个混合整数非线性程序模型，并通过将每辆带有多个站点的车辆视为独立单元来使其线性化。鉴于该问题具有 NP 难度，我们开发了一种量身定制的自适应大邻域搜索（ALNS）方法，通过利用问题的内在结构，有效地解决了实际规模的实例。为了说明所建议的模型和求解方法的效率，我们对不同大小的实例进行了数值实验。结果表明，所开发的 ALNS 算法在解决实际规模的实例时非常有效，能有效处理多达 100 个社区和 14 辆疫苗接种车。此外，一项案例研究表明，与一些基于经验的贪婪方法相比，我们的方法大大降低了运营成本。

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引用次数: 0

Agency selling or reselling: The impact of logistics service on selling mode choice 代理销售还是转售：物流服务对销售模式选择的影响

IF 8.3 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2024-11-11 DOI: 10.1016/j.tre.2024.103849

Gang Li , Zhijun Zheng , T.C.E. Cheng , Wei Wang , Feng Wu

Logistics service affects product sales and therefore plays a vital role in influencing the selling mode strategy. We investigate how two types of logistics service, namely third-party service and platform service, impact the selling mode choice between reselling and agency selling. We identify that the platform’s commission rate and product-service efficiency jointly shape the selling mode strategy. Surprisingly, in a market with third-party service, reselling mitigates double marginalization more than agency selling given high commission rates and product-service efficiency. As a result, the platform favors reselling in situations with relatively low or relatively high commission rates and product-service efficiency, and agency selling for other scenarios. However, in a market with platform service, the platform adopts agency selling (reselling) if product-service efficiency is low (high). Furthermore, we explore how the adoption of platform service changes the selling mode for the platform. Interestingly, we discover that, after the service changes from third-party service to platform service, the selling mode may change from reselling to agency selling (or from agency selling to reselling) in situations with both low commission rates and product-service efficiency (or with high commission rates and medium product-service efficiency). In addition, platform service can benefit both the platform and supplier.

物流服务影响产品销售，因此在影响销售模式战略方面起着至关重要的作用。我们研究了两类物流服务，即第三方服务和平台服务，如何影响转售和代理销售之间的销售模式选择。我们发现，平台佣金率和产品服务效率共同决定了销售模式策略。令人惊讶的是，在有第三方服务的市场中，由于高佣金率和产品服务效率，转售比代理销售更能缓解双重边缘化。因此，在佣金率和产品服务效率相对较低或相对较高的情况下，平台更倾向于转售，而在其他情况下则倾向于代理销售。然而，在有平台服务的市场中，如果产品服务效率低（高），平台就会采用代理销售（转售）。此外，我们还探讨了平台服务的采用如何改变平台的销售模式。有趣的是，我们发现，当服务从第三方服务转变为平台服务后，在低佣金率和产品服务效率（或高佣金率和中等产品服务效率）的情况下，销售模式可能会从转售转变为代理销售（或从代理销售转变为转售）。此外，平台服务可使平台和供应商双方受益。

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引用次数: 0

Trade-in and resale in a platform supply chain: Manufacturer’s choice of selling strategies 平台供应链中的以旧换新和转售：制造商的销售策略选择

IF 8.3 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2024-11-07 DOI: 10.1016/j.tre.2024.103836

Bin Zheng, Yajun Cai, Sijie Li

Trade-in and resale programs are increasingly adopted by retail platforms, boosting sales and generating additional profits through the resale of used products. Consequently, manufacturers selling new products on these platforms should re-evaluate their selling strategies (wholesale or agency). We construct a game-theoretic model to examine when a retail platform should introduce trade-in and resale programs and how a manufacturer should select selling strategy in response. Results indicate that under the wholesale strategy, the introduction of the trade-in and resale program always benefits the retail platform but hurts the manufacturer. However, under the agency strategy, it may positively impact both the retail platform and the manufacturer. Notably, regardless of whether the trade-in and resale program is introduced, the manufacturer should opt for the wholesale strategy if the production cost is high; otherwise, the agency strategy is preferable. Furthermore, after introducing the trade-in and resale program, the manufacturer exhibits a greater inclination towards opting for the agency strategy. This study provides valuable guidance for manufacturers and retail platforms in choosing selling strategies and implementing trade-in and resale programs.

零售平台越来越多地采用以旧换新和转售计划，通过转售旧产品促进销售并创造额外利润。因此，在这些平台上销售新产品的制造商应重新评估其销售策略（批发或代理）。我们构建了一个博弈论模型，以研究零售平台应在何时推出以旧换新和转售计划，以及制造商应如何选择销售策略。结果表明，在批发策略下，以旧换新和转售计划的推出总是有利于零售平台，却损害了制造商的利益。然而，在代理战略下，以旧换新和转售计划可能会对零售平台和制造商都产生积极影响。值得注意的是，无论是否引入以旧换新和转售计划，如果生产成本较高，制造商都应选择批发策略；反之，则应选择代理策略。此外，在引入以旧换新和转售计划后，制造商更倾向于选择代理策略。这项研究为制造商和零售平台选择销售策略、实施以旧换新和转售计划提供了宝贵的指导。

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引用次数: 0

Stack-based yard template generation in automated container terminals under uncertainty 不确定条件下自动化集装箱码头的堆场模板生成

IF 8.3 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2024-11-07 DOI: 10.1016/j.tre.2024.103851

Mingzhong Huang , Junliang He , Hang Yu , Yu Wang

This paper addresses yard template generation problem in automated container terminals when the vessel arrival schedule is uncertain. Since the yard is central to terminal operations, yard management directly affects the efficiency of most equipment. Yard template functions as a tactical-level yard management strategy, allocating yard space to vessels that call at the port on a weekly basis. By analyzing the operational requirements of the various equipment, a yard template is developed in which the stack is the decision unit. Since the yard template will be in operation for an extended period of time, it is critical to account for potential uncertainty. This allows the yard template to effectively manage the yard throughout its duration. Accordingly, a two-stage stochastic programming model is formulated to generate yard template under uncertainty. An improved Benders decomposition algorithm with multiple acceleration strategies is designed to solve the proposed model. The efficiency of the proposed algorithm is validated by numerical experiments. Moreover, some management insights are obtained, such as the impact of uncertain vessel arrival schedule on stack-based yard template and a comparative analysis of stacking strategies in the context of uncertainty.

本文探讨了在船舶抵达时间表不确定的情况下，自动化集装箱码头的堆场模板生成问题。由于堆场是码头运营的核心，因此堆场管理直接影响到大多数设备的效率。堆场模板作为战术层面的堆场管理策略，为每周靠港的船舶分配堆场空间。通过分析各种设备的操作要求，制定出以堆场为决策单元的堆场模板。由于堆场模板将长期运行，因此必须考虑潜在的不确定性。这样，堆场模板就能在整个运营期间有效地管理堆场。因此，我们制定了一个两阶段随机编程模型，以生成不确定情况下的堆场模板。设计了一种具有多种加速策略的改进 Benders 分解算法来求解所提出的模型。通过数值实验验证了所提算法的效率。此外，还获得了一些管理启示，如不确定的船舶抵达时间表对基于堆栈的堆场模板的影响，以及不确定情况下堆栈策略的比较分析。

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引用次数: 0

Meal pickup and delivery problem with appointment time and uncertainty in order cancellation 取餐和送餐问题与预约时间和订单取消的不确定性有关

IF 8.3 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2024-11-06 DOI: 10.1016/j.tre.2024.103845

Guiqin Xue , Zheng Wang , Jiuh-Biing Sheu

Online-ordered meal logistics services (OMLSs) that accept online bookings and make vehicle plans to deliver meals from restaurants to customers have recently emerged. Customers have the option to cancel orders that are not delivered by appointment times, leading to significant financial, reputational, and customer losses for the OMLS providers. This study aims to make an appropriate vehicle plan for OMLS providers to minimize the expected total cost under the uncertainty of order cancellations. The problem is formulated as a two-stage stochastic programming model, and sample average approximation equivalent problems are generated using Monte Carlo simulation. To solve the equivalent problems, a parallel adaptive large neighborhood search (pALNS) with statistical guarantees is developed. Experiment results show that the vehicle plan derived from the ALNS is much better than the solution found by Gurobi within 10,800 s, with an average improvement of 14.90%. Additionally, the pALNS provides better statistical bounds in a shorter time compared to both the ALNS and the unsynchronized pALNS. Analytical experiments reveal that earlier cancellations lead to more severe consequences, offering valuable insights for OMLS providers to implement proactive measures to retain “urgent” customers.

最近出现了在线订餐物流服务（OMLS），这些服务接受在线预订，并制定车辆计划，将餐厅的饭菜送到顾客手中。客户可以选择取消未按预约时间送餐的订单，这给 OMLS 提供商带来了巨大的经济、声誉和客户损失。本研究旨在为 OMLS 提供商制定适当的车辆计划，以便在订单取消的不确定性下最大限度地降低预期总成本。该问题被表述为一个两阶段随机编程模型，并利用蒙特卡罗模拟生成了样本平均近似等效问题。为解决等价问题，开发了一种具有统计保证的并行自适应大邻域搜索（pALNS）。实验结果表明，在 10,800 秒内，ALNS 得出的车辆计划比 Gurobi 找到的解决方案要好得多，平均提高了 14.90%。此外，与 ALNS 和非同步 pALNS 相比，pALNS 能在更短的时间内提供更好的统计边界。分析实验表明，更早的取消会导致更严重的后果，这为 OMLS 提供商采取积极措施留住 "紧急 "客户提供了宝贵的启示。

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引用次数: 0

The rich get richer: Derivative revenue as a catalyst for bike-sharing subscription services 富者愈富：衍生收入是共享单车订购服务的催化剂

IF 8.3 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2024-11-05 DOI: 10.1016/j.tre.2024.103843

Xuan Li , Qing Zheng , Da Ke

By leveraging the derived revenue from subscription services, our study investigates the feasibility of shared bicycle platforms using pricing strategies for these services to enhance their market competitiveness. We establish that, in scenarios where platforms set prices independently, the derived revenue can effectively counterbalance the potential deficits stemming from service expenditures. In a market dominated by exclusive subscription services, an overemphasis on the locking effects can precipitate a mutually detrimental outcome. In a non-exclusive context, the substantial derived revenue can engender a Matthew Effect. Platforms endowed with elevated availability rates are positioned to perpetuate the expansion of their inherent advantages, progressively eroding the market share of their counterparts with diminished availability rates through strategic encroachment. Additionally, we elucidate the strategic dynamics within a competitive platform landscape, underscoring the imperative for platforms to meticulously evaluate their derived revenue scale and devise strategic choices that resonate with their distinctive advantages.

通过利用订阅服务的衍生收入，我们的研究探讨了共享单车平台利用这些服务的定价策略来增强其市场竞争力的可行性。我们发现，在平台独立定价的情况下，衍生收入可以有效抵消服务支出可能产生的赤字。在由独家订阅服务主导的市场中，过分强调锁定效应可能会造成互害的结果。在非独占的情况下，可观的衍生收入会产生马太效应。拥有较高可用率的平台会不断扩大其固有优势，通过战略蚕食逐步侵蚀可用率较低的平台的市场份额。此外，我们还阐明了平台竞争格局中的战略动态，强调平台必须仔细评估其衍生收入规模，并制定与其独特优势相呼应的战略选择。

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引用次数: 0

Distributionally robust optimization for pre-disaster facility location problem with 3D printing 利用 3D 打印技术对灾前设施选址问题进行分布式稳健优化

IF 8.3 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2024-11-05 DOI: 10.1016/j.tre.2024.103844

Peng Sun , Dongpan Zhao , Qingxin Chen , Xinyao Yu , Ning Zhu

The ongoing advancement of 3D printing technology provides an innovative approach to addressing challenges in disaster relief operations. By utilizing a variety of printing materials, 3D printers can produce essential disaster relief resources needed for disaster relief, effectively satisfying the varied demands that arise after disasters. This paper examines the joint optimization of pre-disaster and post-disaster humanitarian operations. Given the significant unpredictability of natural disasters, we introduce a two-stage distributionally robust optimization model to tackle the uncertainty in the demand for various relief resources. The first stage of the model involves decisions related to pre-disaster facility location, 3D printer deployment, and resource allocation. The second stage model addresses the post-disaster rescue activities, including decisions on the production and transportation decisions of relief resources. To address demand uncertainty, we propose an ambiguity set using the Wasserstein metric and reformulate the two-stage distributionally robust optimization model into a tractable formulation. To solve this problem, we employ a Benders decomposition algorithm with an acceleration strategy. The performance of our proposed model and algorithm is evaluated via a real-world case. Numerical experiments reveal that our distributionally robust optimization model outperforms the benchmark model across various metrics. Additionally, we conduct a series of effect analyses and provide managerial insights for decision-makers involved in disaster relief operations.

三维打印技术的不断进步为应对救灾行动中的挑战提供了一种创新方法。通过利用各种打印材料，3D 打印机可以生产出救灾所需的重要救灾资源，有效满足灾后出现的各种需求。本文探讨了灾前和灾后人道主义行动的联合优化问题。鉴于自然灾害具有很大的不可预测性，我们引入了一个两阶段分布稳健优化模型，以应对各种救灾资源需求的不确定性。该模型的第一阶段涉及灾前设施选址、3D 打印机部署和资源分配等相关决策。第二阶段模型涉及灾后救援活动，包括救援资源的生产和运输决策。为解决需求不确定性问题，我们提出了一个使用瓦瑟斯坦度量的模糊集，并将两阶段分布式稳健优化模型重新表述为一个可操作的公式。为了解决这个问题，我们采用了带有加速策略的本德斯分解算法。我们通过实际案例评估了所提模型和算法的性能。数值实验表明，我们的分布稳健优化模型在各种指标上都优于基准模型。此外，我们还进行了一系列效果分析，为参与救灾行动的决策者提供了管理见解。

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引用次数: 0

Traffic Flow Outlier Detection for Smart Mobility Using Gaussian Process Regression Assisted Stochastic Differential Equations 利用高斯过程回归辅助随机微分方程检测智能交通流量异常值

IF 8.3 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2024-11-04 DOI: 10.1016/j.tre.2024.103840

Qixiu Cheng , Guiqi Dai , Bowei Ru , Zhiyuan Liu , Wei Ma , Hongzhe Liu , Ziyuan Gu

Current methods for detecting outliers in traffic streaming data often struggle to capture real-time dynamic changes in traffic conditions and differentiate between genuine changes and anomalies. This study proposes a novel approach to outlier detection in traffic streaming data that effectively addresses stochasticity and uncertainty in observations. The proposed method utilizes Stochastic Differential Equations (SDEs) and Gaussian Process Regression (GPR). By employing SDEs, we can capture drift and diffusion estimates in traffic streaming data, providing a more comprehensive modeling of the data generation process. Integrating GPR allows precise Bayesian posterior inferences for outlier detection within the SDE framework. To improve practicality, we introduce a flexible threshold-setting mechanism using statistical testing to control the false positive rate. This adaptability helps strike a balance between model fitting and complexity in outlier detection. Compared to traditional SDE-based methods, our SDE-GPR outlier detection method demonstrates enhanced robustness and better adaptability to the complexities of traffic systems. This is evidenced through an empirical study using time series data collected in California, USA. Overall, this study introduces a more advanced and accurate approach to outlier detection in traffic streaming data, paving the way for improved real-time traffic condition monitoring and management.

目前在交通流数据中检测异常值的方法往往难以捕捉交通状况的实时动态变化，也难以区分真正的变化和异常。本研究提出了一种在交通流数据中检测异常值的新方法，可有效解决观测中的随机性和不确定性问题。所提出的方法利用了随机微分方程 (SDE) 和高斯过程回归 (GPR)。通过使用 SDE，我们可以捕捉到交通流数据中的漂移和扩散估计，为数据生成过程提供更全面的建模。整合 GPR 可以在 SDE 框架内进行精确的贝叶斯后验推断，从而进行离群点检测。为了提高实用性，我们引入了灵活的阈值设置机制，利用统计测试来控制误报率。这种适应性有助于在离群点检测的模型拟合和复杂性之间取得平衡。与传统的基于 SDE 的方法相比，我们的 SDE-GPR 离群点检测方法显示出更强的鲁棒性和对复杂交通系统的更好适应性。通过使用在美国加利福尼亚州收集的时间序列数据进行实证研究，证明了这一点。总之，本研究为交通流数据中的离群点检测引入了一种更先进、更准确的方法，为改善实时交通状况监控和管理铺平了道路。

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引用次数: 0

Prototype augmentation-based spatiotemporal anomaly detection in smart mobility systems 智能移动系统中基于增强的时空异常检测原型

IF 8.3 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2024-11-03 DOI: 10.1016/j.tre.2024.103815

Zhen Zhou , Ziyuan Gu , Anfeng Jiang , Zhiyuan Liu , Yi Zhao , Hongzhe Liu

In complex mobility systems, the widespread presence of spatiotemporal anomaly patterns poses substantial challenges to effective governance and decision-making. A notable example of this challenge is evident in traffic anomalous incidents detection, where the combination of low accuracy in anomaly detection and poor scenario generalization performance significantly impacts the overall performance of anomaly detection. This paper introduces a prototype augmentation-based framework tailored for spatiotemporal anomaly detection in the context of smart mobility system. This framework utilizes prototype augmentation technique to enhance the diversity of anomaly patterns, ensuring that the integrity of the original anomaly information is preserved. Essentially, the prototype augmentation-based anomaly detector employed in this framework is a hybrid unsupervised-supervised stacking ensemble. It leverages the strengths of unsupervised component learners to generate pseudo dimensions while integrating a supervised meta-detector for evaluating the component learners’ performance across diverse environmental contexts. Additionally, we materialize this framework and assess its performance in detecting anomalous line-pressing incidents. Empirical results demonstrate our framework’s superior accuracy and transferability in detecting anomalous traffic incidents compared to alternative methods using a real-world dataset.

在复杂的交通系统中，时空异常模式的广泛存在给有效的治理和决策带来了巨大挑战。交通异常事件检测就是这一挑战的一个明显例子，异常检测的低准确率和糟糕的场景泛化性能严重影响了异常检测的整体性能。本文介绍了一个基于原型增强的框架，该框架专为智能移动系统中的时空异常检测而定制。该框架利用原型增强技术来提高异常模式的多样性，同时确保保留原始异常信息的完整性。从本质上讲，本框架采用的基于原型增强的异常检测器是一种无监督-监督混合堆叠集合。它利用无监督组件学习器的优势生成伪维度，同时集成了一个监督元检测器，用于评估组件学习器在不同环境背景下的性能。此外，我们还将这一框架具体化，并评估其在检测异常压线事件方面的性能。实证结果表明，与使用真实世界数据集的其他方法相比，我们的框架在检测异常交通事故方面具有更高的准确性和可移植性。

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引用次数: 0