Journal of Korean Society of Transportation ISSN:1229-1366(Print) 2234-4217(Online) 대한교통학회지

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Alvarez J. A., Legler P. M., Dean S. N., Malanoski A. P., Naval Research Lab Washington DC. (2022), Applying Machine Learning with Model Interpretability for Sequence-based Protein Solubility Prediction.

Amini M., Bagheri A., Delen D. (2022), Discovering Injury Severity Risk Factors in Automobile Crashes: A Hybrid Explainable AI Framework for Decision Support, Reliab. Eng. Syst. Saf., 226, 108720.

Ashraf M. T., Dey K., Mishra S. (2023), Identification of High-risk Roadway Segments for Wrong-way Driving Crash using Rare Event Modeling and Data Augmentation Techniques, Accid. Anal. Prev., 181, 106933.

Azevêdo L., Duarte H., Galvão D., Michima P., Veleda D., Kreuger A. (2021), Methodology for Maritime Risk Assessment in Ports due to Meteo-oceanographic Factors: The Case of the Port of Suape, Brazil, Risk Anal., 41(10), 1823-1839.

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Islam Z., Abdel-Aty M., Cai Q., Yuan J. (2021), Crash data augmentation using variational autoencoder, Accid. Anal. Prev., 151, 105950.

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Jeong H., Jang Y., Bowman P. J., Masou, N. (2018), Classification of Motor Vehicle Crash Injury Severity: A Hybrid Approach for Imbalanced Data, Accident Analysis & Prevention, 120, 250-261.

Khan R. U., Yin J., Mustafa F. S., Farea A. O. A. (2022), A Data Centered Human Factor Analysis Approach for Hazardous Cargo Accidents in a Port Environment, J. Loss Prev. Process Ind., 75, 104711.

Kim D. H., Kim J. T. (2021), Development and Evaluation of LoT-based Conflict Prediction Model for Real-time Prevention of Vehicle Accident at Port Yard Intersection, J. Korean Soc. Transp., 39(4), Korean Society of Transportation, 516-525.

Korea Maritime Institute (2021), Development of Countermeasures at Ports Following the Enforcement of the Serious Accidents Punishment Act.

Lee S., Kim S., Kim J., Kim D., Heo T. Y. (2023), Multiclass Classification by Various Machine Learning Algorithms and Interpretation of the Risk Factors of Pedestrian Accidents using Explainable AI, Math. Probl. Eng., 29, 1-15

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Madushani J. S., Sandamal R. K., Meddage D. P. P., Pasindu H. R., Gomes P. A. (2023), Evaluating Expressway Traffic Crash Severity by using Logistic Regression and Explainable & Supervised Machine Learning Classifiers, Transp. Eng., 13, 100190.

Menardi G., Torelli N. (2014), Training and Assessing Classification Rules with Imbalanced Data, Data Min. Knowl. Discov., 28, 92-122.

Min G., Ka D., Chung S., Lee C. (2023), Development of an Explainable Traffic Flow Prediction Model using SHapley Additive exPlanation and elliptic bivariate relationship, J. Korean Soc. Transp., 41(2), Korean Society of Transportation, 239-253.

Morris C., Yang J. J. (2021), Effectiveness of Resampling Methods in Coping with Imbalanced Crash Data: Crash type Analysis and Predictive Modeling, Accid. Anal. Prev., 159, 106240.

Park N. (2023), Assessment of Crash Risk Situations using Bayesian Inference and Machine Learning Techniques, Master's thesis, Hanyang University.

Qiao W., Liu Y., Ma X., Liu Y. (2020), Human Factors Analysis for Maritime Accidents Based on a Dynamic Fuzzy Bayesian Network, Risk Anal., 40(5), 957-980.

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Son S. O., Kim H., Park J. (2020), Methodology of Calibration for Falling Objects Accident-risk-zone Approach Detection Algorithm at Port Considering GPS Errors, J. Korean Inst. Intell. Transp. Syst., 19(6), 61-73.

Son S. O., Park J., Oh C., Yeom C. (2021), An Algorithm for Detecting Collision Risk between Trucks and Pedestrians in the Connected Environment, J. Adv. Transp., 2021, 1-9.

Uğurlu Ö., Yıldız S., Loughney S., Wang J., Sharabidze I. (2020), Analyzing Collision, Grounding, and Sinking Accidents Occurring in the Black Sea utilizing HFACS and Bayesian networks, Risk Anal., 40(12), 2610-2638.

Wen X., Xie Y., Jiang L., Pu Z., Ge T. (2021a), Applications of Machine Learning Methods in Traffic Crash Severity Modelling: Current Status and Future Directions, Transp. Rev., 41(6), 855-879.

Wen X., Xie Y., Wu L., Jiang L. (2021b), Quantifying and Comparing the Effects of Key Risk Factors on Various Types of Roadway Segment Crashes with LightGBM and SHAP, Accid. Anal. Prev., 159, 106261.

Yang C., Chen M., Yuan Q. (2021), The Application of XGBoost and SHAP to Examining the Factors in Freight Truck-related Crashes: An Exploratory Analysis, Accid. Anal. Prev., 158, 106153.

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Zhang, J., Chen, L. (2019), Clustering-based undersampling with random over sampling examples and support vector machine for imbalanced classification of breast cancer diagnosis, Comput. Assist. Surg., 24(sup2), 62-72.

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Zhu L., Zhang Z., Song D., Chen B. (2024), Analysis of Traffic Accident Causes Based on Data Augmentation and Ensemble Learning with High-dimensional Small-sample Data, Expert Systems with Applications, 237, 121782.