Transportmetrica A-Transport Science最新文献

英文中文

Diversity-oriented dynamic ensemble selection approach for multi-class road traffic injury severity predictions with interpretable insights 面向多样性的多类别道路交通伤害严重程度预测的动态集成选择方法

IF 3.1 2区工程技术 Q2 TRANSPORTATION

Transportmetrica A-Transport Science

Pub Date : 2026-01-02 DOI: 10.1080/23249935.2025.2542283

Kamran Aziz , Feng Chen , Inamullah Khan , Zahid Ullah , Mona Jamjoom , Muhammad Imran Khan

Accurately predicting crash injury severity in multi-class settings is vital for improving road safety, as different injury levels require tailored interventions. This study explores the effectiveness of Dynamic Ensemble Selection (DES) combined with Static Ensemble Selection (SES) classifiers for multi-class injury severity prediction. We employ diversity-driven DES methods—DES-KNN and DES-Clustering—alongside classifiers such as Extra Trees, AdaBoost, and XG-Boost. To address data imbalance, SMOTE and its variants are applied for equitable class representation. Results show that DES-KNN with XG-Boost, using SMOTE preprocessed data, achieves the best performance with a Balanced Accuracy Score of 0.56, G-Mean of 0.66, and MCC of 0.26. Additionally, LIME is used to interpret model predictions and enhance transparency by highlighting influential features. Our findings demonstrate that integrating DES with SES classifiers significantly improves predictive performance and interpretability, highlighting DES as a valuable approach for handling imbalanced multi-class crash severity data in support of sustainable transportation strategies.

准确预测多类别环境中的碰撞损伤严重程度对于提高道路安全至关重要，因为不同的伤害级别需要量身定制的干预措施。本研究探讨了动态集合选择（DES）与静态集合选择（SES）分类器在多类别损伤严重程度预测中的有效性。我们采用了多样性驱动的DES方法——DES- knn和DES- clustering——以及Extra Trees、AdaBoost和XG-Boost等分类器。为了解决数据不平衡问题，SMOTE及其变体被应用于公平的类表示。结果表明，使用SMOTE预处理数据的XG-Boost的DES-KNN达到了最佳性能，其平衡精度得分为0.56，G-Mean为0.66，MCC为0.26。此外，LIME用于解释模型预测，并通过突出显示有影响的特征来提高透明度。我们的研究结果表明，将DES与SES分类器集成可以显著提高预测性能和可解释性，强调DES是处理不平衡的多类别碰撞严重程度数据以支持可持续交通策略的有价值的方法。

{"title":"Diversity-oriented dynamic ensemble selection approach for multi-class road traffic injury severity predictions with interpretable insights","authors":"Kamran Aziz , Feng Chen , Inamullah Khan , Zahid Ullah , Mona Jamjoom , Muhammad Imran Khan","doi":"10.1080/23249935.2025.2542283","DOIUrl":"10.1080/23249935.2025.2542283","url":null,"abstract":"<div><div>Accurately predicting crash injury severity in multi-class settings is vital for improving road safety, as different injury levels require tailored interventions. This study explores the effectiveness of Dynamic Ensemble Selection (DES) combined with Static Ensemble Selection (SES) classifiers for multi-class injury severity prediction. We employ diversity-driven DES methods—DES-KNN and DES-Clustering—alongside classifiers such as Extra Trees, AdaBoost, and XG-Boost. To address data imbalance, SMOTE and its variants are applied for equitable class representation. Results show that DES-KNN with XG-Boost, using SMOTE preprocessed data, achieves the best performance with a Balanced Accuracy Score of 0.56, G-Mean of 0.66, and MCC of 0.26. Additionally, LIME is used to interpret model predictions and enhance transparency by highlighting influential features. Our findings demonstrate that integrating DES with SES classifiers significantly improves predictive performance and interpretability, highlighting DES as a valuable approach for handling imbalanced multi-class crash severity data in support of sustainable transportation strategies.</div></div>","PeriodicalId":48871,"journal":{"name":"Transportmetrica A-Transport Science","volume":"22 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146071084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Logistics vehicle routing optimisation with synchronised transfer 同步转移的物流车辆路线优化

IF 3.1 2区工程技术 Q2 TRANSPORTATION

Transportmetrica A-Transport Science

Pub Date : 2026-01-02 DOI: 10.1080/23249935.2024.2355954

Shuai Wang , Xiaoning Zhu , Siyu Zhuo , Pan Shang

This paper presents a synchronized transfer strategy in which operators can schedule logistics vehicles among employees and arrange the transfer of commodities. The transfer time consists of the vehicle waiting time and commodity transition time. By adopting the strategy, logistics vehicles can visit fewer communities, resulting in savings in transportation cost under ensuring punctual delivery. An integer programming model based on a space-time-state network is proposed to describe the complex transfer process. To simplify the model, time window and vehicle capacity constraints are embedded into the network. The alternating direction method of multipliers (ADMM) is designed to solve the model. In the ADMM-based solution framework, the original model can be converted into a series of shortest-path searching subproblems and iteratively solved using a dynamic programming (DP) algorithm. Our computational results show that the proposed model and algorithm are efficient and competitive.

本文提出了一种同步转运策略，在这种策略中，运营商可以在员工之间调度物流车辆，安排商品转运。转运时间由转运时间和转运时间之间的...

引用次数: 0

Customised bus service design considering flexible vehicle size and transfer incentivization 考虑到灵活的车辆尺寸和换乘激励措施的定制公交服务设计

IF 3.1 2区工程技术 Q2 TRANSPORTATION

Transportmetrica A-Transport Science

Pub Date : 2026-01-02 DOI: 10.1080/23249935.2024.2388618

Jianbiao Wang , Tomio Miwa , Dawei Li , Takayuki Morikawa

In this study, the flexible vehicle size and transfer incentivization strategies are incorporated to increase the potential of the customised bus system. In detail, the modular vehicle system is adopted for flexible vehicle size design since it can be connected as the assembled bus in response to demand variation. Also, the transfer among buses is considered to group passengers with the same destinations to increase bus utilisation. However, the passengers will not actively transfer as it is viewed as a disutility. Thus, the incentivization is provided and the transfer demand is elastic under incentivization. We jointly optimise passenger-route assignment, vehicle size, and incentivization scheme by transforming the original nonlinear programming model into a mixed integer linear programming model. Then, to solve the larger case study, the modified ant colony system algorithm is also proposed. The experiments validate the superiority of customised bus service considering flexible vehicle size and transfer incentivization.

在这项研究中，灵活的车辆尺寸和换乘激励策略被纳入其中，以提高定制公交系统的潜力。具体来说，模块化的车辆系统是一种...

引用次数: 0

In loving memory of Professor Richard Allsop: a great loss to HKSTS and the transportation community 深切缅怀理查德-艾尔索普教授：香港科技学院和交通运输界的重大损失

IF 3.1 2区工程技术 Q2 TRANSPORTATION

Transportmetrica A-Transport Science

Pub Date : 2026-01-02 DOI: 10.1080/23249935.2024.2338993

S. C. Wong (Professor)

引用次数: 0

Correlation-based feature selection and parallel spatiotemporal networks for efficient passenger flow forecasting in metro systems 基于相关性的特征选择和并行时空网络用于地铁系统的高效客流预测

IF 3.1 2区工程技术 Q2 TRANSPORTATION

Transportmetrica A-Transport Science

Pub Date : 2026-01-02 DOI: 10.1080/23249935.2024.2335244

Cong Xiu , Shuguang Zhan , Jinyi Pan , Qiyuan Peng , Zhiyuan Lin , S.C. Wong

This paper presents a novel framework for predicting metro passenger flow that is both interpretable and computationally efficient. The proposed method first uses a correlation-based spatiotemporal feature selection strategy (Cor-STFS) to identify the optimal input scheme for the prediction model, effectively reducing unnecessary interference. The framework then introduces a new multivariate passenger flow prediction architecture called STA-PTCN-BiGRU, which combines a spatiotemporal attention (STA) mechanism, parallel temporal convolutional networks (PTCN), and bidirectional gated recurrent units (BiGRU) to capture the dynamic internal patterns of passenger flow. By utilising parallel computing, this architecture significantly reduces resource consumption. The effectiveness of the proposed approach is evaluated using four datasets from the Shanghai Metro. Experimental results show that the new method outperforms baseline approaches in terms of root mean square error (RMSE), mean absolute error (MAE), and symmetric mean absolute percentage error (SMAPE), achieving average reductions of 9.98%, 8.08%, and 13.29% in these metrics, respectively.

本文提出了一种新颖的地铁客流预测框架，该框架既可解释，又具有计算效率。所提出的方法首先使用基于相关性的时空...

{"title":"Correlation-based feature selection and parallel spatiotemporal networks for efficient passenger flow forecasting in metro systems","authors":"Cong Xiu , Shuguang Zhan , Jinyi Pan , Qiyuan Peng , Zhiyuan Lin , S.C. Wong","doi":"10.1080/23249935.2024.2335244","DOIUrl":"10.1080/23249935.2024.2335244","url":null,"abstract":"<div><div>This paper presents a novel framework for predicting metro passenger flow that is both interpretable and computationally efficient. The proposed method first uses a correlation-based spatiotemporal feature selection strategy (Cor-STFS) to identify the optimal input scheme for the prediction model, effectively reducing unnecessary interference. The framework then introduces a new multivariate passenger flow prediction architecture called STA-PTCN-BiGRU, which combines a spatiotemporal attention (STA) mechanism, parallel temporal convolutional networks (PTCN), and bidirectional gated recurrent units (BiGRU) to capture the dynamic internal patterns of passenger flow. By utilising parallel computing, this architecture significantly reduces resource consumption. The effectiveness of the proposed approach is evaluated using four datasets from the Shanghai Metro. Experimental results show that the new method outperforms baseline approaches in terms of root mean square error (RMSE), mean absolute error (MAE), and symmetric mean absolute percentage error (SMAPE), achieving average reductions of 9.98%, 8.08%, and 13.29% in these metrics, respectively.</div></div>","PeriodicalId":48871,"journal":{"name":"Transportmetrica A-Transport Science","volume":"22 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140594901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Toll road crash severity using mixed logit model incorporating heterogeneous mean structures 使用包含异质平均结构的混合对数模型计算收费公路车祸严重程度

IF 3.1 2区工程技术 Q2 TRANSPORTATION

Transportmetrica A-Transport Science

Pub Date : 2026-01-02 DOI: 10.1080/23249935.2024.2343755

Subasish Das , Monire Jafari , Ahmed Hossain , Rohit Chakraborty , Mahmuda Sultana Mimi

The current study examined 1,465 crash observations (2017–2021) from Louisiana, identifying significant variables grouped into three major categories: drivers’, crash, and road characteristics. Considering crash injury severity as a dependent variable, we employed classic Multinomial Logit (MNL) model, and several other models to address unobserved heterogeneity in crash data including Random Parameter Logit (RPL), Random Parameter Logit with Heterogeneity in Means (RPLHM), and Random Parameter Logit with Heterogeneity in Means and Variance (RPLHMV). Our findings highlight the impact of factors such as driver gender, age, traffic violations, driver distractions, crash types, surface conditions, and roadway attributes on crash injury severity. These insights emphasise the complexity of toll road safety and inform targeted interventions to mitigate crash injury severity. Notably, male drivers and those under 25 years old increased property damage likelihood, while factors like driver distractions and lower posted speed limits reduced the likelihood of severe injuries or fatalities.

本研究对路易斯安那州的 1465 项碰撞观测数据（2017-2021 年）进行了研究，确定了分为三大类的重要变量：驾驶员、碰撞和道路特征。碰撞...

{"title":"Toll road crash severity using mixed logit model incorporating heterogeneous mean structures","authors":"Subasish Das , Monire Jafari , Ahmed Hossain , Rohit Chakraborty , Mahmuda Sultana Mimi","doi":"10.1080/23249935.2024.2343755","DOIUrl":"10.1080/23249935.2024.2343755","url":null,"abstract":"<div><div>The current study examined 1,465 crash observations (2017–2021) from Louisiana, identifying significant variables grouped into three major categories: drivers’, crash, and road characteristics. Considering crash injury severity as a dependent variable, we employed classic Multinomial Logit (MNL) model, and several other models to address unobserved heterogeneity in crash data including Random Parameter Logit (RPL), Random Parameter Logit with Heterogeneity in Means (RPLHM), and Random Parameter Logit with Heterogeneity in Means and Variance (RPLHMV). Our findings highlight the impact of factors such as driver gender, age, traffic violations, driver distractions, crash types, surface conditions, and roadway attributes on crash injury severity. These insights emphasise the complexity of toll road safety and inform targeted interventions to mitigate crash injury severity. Notably, male drivers and those under 25 years old increased property damage likelihood, while factors like driver distractions and lower posted speed limits reduced the likelihood of severe injuries or fatalities.</div></div>","PeriodicalId":48871,"journal":{"name":"Transportmetrica A-Transport Science","volume":"22 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140610480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Lane change decision prediction: an efficient BO-XGB modelling approach with SHAP analysis 车道变更决策预测：采用 SHAP 分析的高效 BO-XGB 建模方法

IF 3.1 2区工程技术 Q2 TRANSPORTATION

Transportmetrica A-Transport Science

Pub Date : 2026-01-02 DOI: 10.1080/23249935.2024.2372020

Haobo Sun , Qixiu Cheng , Pu Wang , Yongqi Huang , Zhiyuan Liu

The lane-change decision (LCD) is a critical aspect of driving behaviour. This study proposes an LCD model based on a Bayesian optimization (BO) framework and extreme gradient boosting (XGBoost) to predict whether a vehicle should change lanes. First, an LCD point extraction method is proposed to refine the exact LCD points with a highD dataset to increase model learning accuracy. Subsequently, an efficient XGBoost with BO (BO-XGB) was used to learn the LCD principles. The prediction accuracy on the highD dataset was 99.14% with a computation time of 66.837s. The accuracy on the CQSkyEyeX dataset was 99.45%. Model explanation using the shapley additive explanation (SHAP) method was developed to analyse the mechanism of the BO-XGB’s LCD prediction results, including global and sample explanations. The former indicates the particular contribution of each feature to the model prediction throughout the entire dataset. The latter denotes each feature's contribution to a single sample.

变道决策（LCD）是驾驶行为的一个重要方面。本研究提出了一种基于贝叶斯优化（BO）框架和极端梯度提升（XGBoost）的 LCD 模型，以...

引用次数: 0

Investigating older driver crashes on high-speed roadway segments: a hybrid approach with extreme gradient boosting and random parameter model 高速路段老龄驾驶员碰撞事故调查：采用极端梯度提升和随机参数模型的混合方法

IF 3.1 2区工程技术 Q2 TRANSPORTATION

Transportmetrica A-Transport Science

Pub Date : 2026-01-02 DOI: 10.1080/23249935.2024.2362362

Ahmed Hossain , Xiaoduan Sun , Subasish Das , Monire Jafari , Julius Codjoe

Older drivers are often more susceptible to crashes due to age-related physical and cognitive limitations, particularly in complex driving environments. Considering the limited research in this area, this study focuses on investigating crashes involving older drivers on high-speed roadways (≥ 45 mph). The analysis is based on data collected from Louisiana State, encompassing 18,300 older driver-involved crashes (2017-2021). For analysis, a two-step hybrid modelling approach is employed: a) Extreme Gradient Boosting (XGBoost) is used to classify top variable features and b) Correlated Random Parameter Ordered Probit with Heterogeneity in Means (CRPOP-HM) is used to predict the likelihood of crash injury severity. . Some of the critical factors increasing the likelihood of fatal-severe or injury crashes involving older drivers on high-speed segments include the manner of collision (rear-end, right-angle, single-vehicle), primary contributing factor (violation, pedestrian action), presence of passenger (s), location type (open country, residential, business with mixed residential), and weekend.

由于与年龄有关的身体和认知限制，老年驾驶员往往更容易发生车祸，尤其是在复杂的驾驶环境中。考虑到这方面的研究有限...

{"title":"Investigating older driver crashes on high-speed roadway segments: a hybrid approach with extreme gradient boosting and random parameter model","authors":"Ahmed Hossain , Xiaoduan Sun , Subasish Das , Monire Jafari , Julius Codjoe","doi":"10.1080/23249935.2024.2362362","DOIUrl":"10.1080/23249935.2024.2362362","url":null,"abstract":"<div><div>Older drivers are often more susceptible to crashes due to age-related physical and cognitive limitations, particularly in complex driving environments. Considering the limited research in this area, this study focuses on investigating crashes involving older drivers on high-speed roadways (≥ 45 mph). The analysis is based on data collected from Louisiana State, encompassing 18,300 older driver-involved crashes (2017-2021). For analysis, a two-step hybrid modelling approach is employed: a) Extreme Gradient Boosting (XGBoost) is used to classify top variable features and b) Correlated Random Parameter Ordered Probit with Heterogeneity in Means (CRPOP-HM) is used to predict the likelihood of crash injury severity. . Some of the critical factors increasing the likelihood of fatal-severe or injury crashes involving older drivers on high-speed segments include the manner of collision (rear-end, right-angle, single-vehicle), primary contributing factor (violation, pedestrian action), presence of passenger (s), location type (open country, residential, business with mixed residential), and weekend.</div></div>","PeriodicalId":48871,"journal":{"name":"Transportmetrica A-Transport Science","volume":"22 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141548599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

MicroSimACC: an open database for field experiments on the potential capacity impact of commercial Adaptive Cruise Control (ACC) MicroSimACC：商用自适应巡航控制系统（ACC）潜在容量影响现场实验开放数据库

IF 3.1 2区工程技术 Q2 TRANSPORTATION

Transportmetrica A-Transport Science

Pub Date : 2026-01-02 DOI: 10.1080/23249935.2024.2349921

Mingyuan Yang , Pablo Chon-Kan Munoz , Servet Lapardhaja , Yaobang Gong , Md. Ashraful Imran , Md. Tausif Murshed , Kemal Yagantekin , Md. Mahede Hasan Khan , Xingan (David) Kan , Choungryeol Lee

Commercial availability of vehicle automation has become mainstream. Most of today’s new vehicles can perform longitudinal car following autonomously via Adaptive Cruise Control (ACC). Field experiments demonstrate that today’s commercially available ACC vehicles provide similar headways and capacities as human-driven vehicles on freeways under steady-state and free-flow conditions. However, field tests also demonstrated that the design of today’s commercially available ACC vehicles can lead to further capacity reduction when operating in non-steady-state conditions where queues are present and speeds frequently fluctuate. These experiments generated MicroSimACC, a comprehensive set of field data that encompasses full speed range car following with interruptions from lane change manoeuvres. This will benefit the research community by providing benchmark data for developing models to be integrated into microscopic simulations for more prospective analyses and planning.

汽车自动化的商业应用已成为主流。如今，大多数新车都能通过自适应巡航控制系统（ACC）自动执行纵向跟车。实地体验

{"title":"MicroSimACC: an open database for field experiments on the potential capacity impact of commercial Adaptive Cruise Control (ACC)","authors":"Mingyuan Yang , Pablo Chon-Kan Munoz , Servet Lapardhaja , Yaobang Gong , Md. Ashraful Imran , Md. Tausif Murshed , Kemal Yagantekin , Md. Mahede Hasan Khan , Xingan (David) Kan , Choungryeol Lee","doi":"10.1080/23249935.2024.2349921","DOIUrl":"10.1080/23249935.2024.2349921","url":null,"abstract":"<div><div>Commercial availability of vehicle automation has become mainstream. Most of today’s new vehicles can perform longitudinal car following autonomously via Adaptive Cruise Control (ACC). Field experiments demonstrate that today’s commercially available ACC vehicles provide similar headways and capacities as human-driven vehicles on freeways under steady-state and free-flow conditions. However, field tests also demonstrated that the design of today’s commercially available ACC vehicles can lead to further capacity reduction when operating in non-steady-state conditions where queues are present and speeds frequently fluctuate. These experiments generated MicroSimACC, a comprehensive set of field data that encompasses full speed range car following with interruptions from lane change manoeuvres. This will benefit the research community by providing benchmark data for developing models to be integrated into microscopic simulations for more prospective analyses and planning.</div></div>","PeriodicalId":48871,"journal":{"name":"Transportmetrica A-Transport Science","volume":"22 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140931767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Headway regularity as an attribute for classifying bus drivers 作为公交车司机分类属性的班次间隔规律性

IF 3.1 2区工程技术 Q2 TRANSPORTATION

Transportmetrica A-Transport Science

Pub Date : 2026-01-02 DOI: 10.1080/23249935.2024.2337737

Yerly Martínez-Estupiñan , Felipe Delgado , Juan Carlos Muñoz

Different indices have been proposed in the literature to characterize headway regularity. These metrics aggregate the headway variability for a service, but none can be directly associated with a specific driver. This paper seeks to understand drivers' influence on a service's regularity. To do so, we propose four regularity indices related to a driver's performance and use the Hierarchical Clustering Analysis method to generate a classification of drivers according to their contribution to the headway regularity during the operation of a service. We characterize each class based on the driver's attributes such as age, years of experience as a driver, and years in the bus company, and those attributes associated with the operation, such as number of services per day and period of the day. The results show consistency in the classification obtained, with nearly 90% of drivers remaining in the same regularity classes regardless of the index.

文献中提出了不同的指标来描述班次间隔的规律性。这些指标汇总了某一服务的班次间隔变化情况，但都不能直接与班次间隔相关联。

引用次数: 0

下一页尾页

类型

全部化学•材料生命科学医学物理工程技术环境•农林材料科学地球科学法学管理学化学环境科学与生态学计算机科学教育学经济学农林科学人文科学生物学数学物理与天体物理心理学综合性期刊其他工业工程理学历史学农学文学信息工程

数据库

全部 ACS Publications Elsevier ieeexplore Springer The Royal Society of Chemistry Wiley

期刊

Transportmetrica A-Transport Science

全部 Acc. Chem. Res. ACS Applied Bio Materials ACS Appl. Electron. Mater. ACS Appl. Energy Mater. ACS Appl. Mater. Interfaces ACS Appl. Nano Mater. ACS Appl. Polym. Mater. ACS BIOMATER-SCI ENG ACS Catal. ACS Cent. Sci. ACS Chem. Biol. ACS Chemical Health & Safety ACS Chem. Neurosci. ACS Comb. Sci. ACS Earth Space Chem. ACS Energy Lett. ACS Infect. Dis. ACS Macro Lett. ACS Mater. Lett. ACS Med. Chem. Lett. ACS Nano ACS Omega ACS Photonics ACS Sens. ACS Sustainable Chem. Eng. ACS Synth. Biol. Anal. Chem. BIOCHEMISTRY-US Bioconjugate Chem. BIOMACROMOLECULES Chem. Res. Toxicol. Chem. Rev. Chem. Mater. CRYST GROWTH DES ENERG FUEL Environ. Sci. Technol. Environ. Sci. Technol. Lett. Eur. J. Inorg. Chem. IND ENG CHEM RES Inorg. Chem. J. Agric. Food. Chem. J. Chem. Eng. Data J. Chem. Educ. J. Chem. Inf. Model. J. Chem. Theory Comput. J. Med. Chem. J. Nat. Prod. J PROTEOME RES J. Am. Chem. Soc. LANGMUIR MACROMOLECULES Mol. Pharmaceutics Nano Lett. Org. Lett. ORG PROCESS RES DEV ORGANOMETALLICS J. Org. Chem. J. Phys. Chem. J. Phys. Chem. A J. Phys. Chem. B J. Phys. Chem. C J. Phys. Chem. Lett. Analyst Anal. Methods Biomater. Sci. Catal. Sci. Technol. Chem. Commun. Chem. Soc. Rev. CHEM EDUC RES PRACT CRYSTENGCOMM Dalton Trans. Energy Environ. Sci. ENVIRON SCI-NANO ENVIRON SCI-PROC IMP ENVIRON SCI-WAT RES Faraday Discuss. Food Funct. Green Chem. Inorg. Chem. Front. Integr. Biol. J. Anal. At. Spectrom. J. Mater. Chem. A J. Mater. Chem. B J. Mater. Chem. C Lab Chip Mater. Chem. Front. Mater. Horiz. MEDCHEMCOMM Metallomics Mol. Biosyst. Mol. Syst. Des. Eng. Nanoscale Nanoscale Horiz. Nat. Prod. Rep. New J. Chem. Org. Biomol. Chem. Org. Chem. Front. PHOTOCH PHOTOBIO SCI PCCP Polym. Chem.

﹀