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

Awasthi S. (2020), Random Forests in Machine Learning: A Detailed Explanation, datamahadev.com.

Brownlee J. (2020), Imbalanced Classification with Python: Better Metrics, Balance Skewed Classes, Cost-sensitive Learning, Machine Learning Mastery.

Champahom T., Jomnonkwao S., Watthanaklang D., Karoonsoontawong A., Chatpattananan V., Ratanavaraha V. (2020), Applying Hierarchical Logistic Models to Compare Urban and Rural Roadway Modeling of Severity of Rear-end Vehicular Crashes, Accident Analysis and Prevention, 141, 105537.

Chen T., Guestrin C. (2016), Xgboost: A Scalable Tree Boosting system, In Proceedings of the 22nd Acm Sigkdd International Conference on Knowledge Discovery and Data mining, 785-794.

Cho E.S., Jo Y., Gu, Y. S., Oh C., Lee G. W. (2023), Detection of Risk Riding Events for Delivery Scooter : Methodology and Application, J. Korean Soc. Transp., 41(1), Korean Society of Transportation, 19-34.

Chung D. H., Yun J. S., Yang S. M. (2021), Machine Learning for Predicting Entrepreneurial Innovativeness, Asia-Pacific, Journal of Business Venturing and Entrepreneurship, 16(3), 73-86.

Khan K., Ahmad W., Amin M. N., Ahmad A., Nazar S., Alabdullah A. A. (2022), Compressive Strength Estimation of Steel-fiber-reinforced Concrete and Raw Material Interactions using Advanced Algorithms, Polymers, 14(15), 3065.

Khattak M. W., Pirdavani A., De Winne P., Brijs T., De Backer H. (2021), Estimation of Safety Performance Functions for Urban Intersections using Various Functional Forms of the Negative Binomial Regression Model and a Generalized Poisson Regression Model, Accident Analysis and Prevention, 151, 105964.

Kidando E., Kitali A. E., Kutela B., Karaer A., Ghorbanzadeh M., Koloushani M., Ozguven E. E. (2022), Use of Real-time Traffic and Signal Timing Data in Modeling Occupant Injury Severity at Signalized Intersections, Transportation Research Record, 2676(2), 825-839.

Korea Road Traffic Authority (2023), Estimation and Evaluation of Road Traffic Accident Costs.

Lee K. Y., Kim Y. S. (2021), Predictive Model for the Employment Retention of Persons with Disabilities, Journal of Special Education, 37(2), 73-95.

Lee M. W., Kim, Y. G., Jun Y. J., Shin Y. H. (2019), Random Forest based Prediction of Road Surface Condition Using Spatio-Temporal Features, J. Korean Soc. Transp., 37(4), Korean Society of Transportation, 338-349.

Lin W., Wu Z., Lin L., Wen A., Li J. (2017), An Ensemble Random Forest Algorithm for Insurance Big Data Analysis, Ieee Access, 5, 16568-16575.

Mitra S., Bhowmick D. (2020), Status of Signalized Intersection Safety-a Case Study of Kolkata, Accident Analysis and Prevention, 141, 105525.

Park B. H., In B. C. (2009), Rear-end Accident Models of Rural Area Signalized Intersections in the Cases of Cheongju and Cheongwon, International Journal of Highway Engineering, 11(2), 151-158.

Park B. H., Park J. S. (2007), Analysis of Rear-End Accidents at 4-legged Signalized Intersections in Cheongju, J. Korean Soc. Transp., 25(5), Korean Society of Transportation, 57-66.

Park J. H., Lee G. W., Oh C., Kim J. H., Yun D. G. (2021), Development of Evaluation Methodology for Rear Collision Situation Using Vehicle Sensor Data, J. Korean Soc. Transp., 39(6), Korean Society of Transportation, 826-837.

Sandri M., Zoccolotto P. (2010), Analysis and Correction of Bias in Total Decrease in Node Impurity Measures for Tree-based Algorithms, Statistics and Computing, 20(4), 393-407.

Sharafeldin M., Farid A., Ksaibati K. (2022a), Investigating the Impact of Roadway Characteristics on Intersection Crash Severity, Eng, 3(4), 412-423.

Sharafeldin M., Farid A., Ksaibati K. (2022b), Injury Severity Analysis of Rear-End Crashes at Signalized Intersections, Sustainability, 14(21), 13858.

Son S. O., Park J. Y. (2022), Assessment of Crash Prediction Models for Intersections with Severity Weight Parameters Using Data Science Approaches, J. Korean Soc. Transp., 40(2), Korean Society of Transportation, 190-204.

Virnodkar S. S., Pachghare V. K., Patil V. C., Jha S. K. (2020), Remote Sensing and Machine Learning for Crop Water Stress Determination in Various Crops: A Critical Review, Precision Agriculture, 21(5), 1121-1155.

Wang X., Abdel-Aty M. (2006), Temporal and Spatial Analyses of Rear-end Crashes at Signalized Intersections, Accident Analysis and Prevention, 38(6), 1137-1150.

Wang Y., Ieda H., Mannering F. (2003), Estimating Rear-end Accident Probabilities at Signalized Intersections: Occurrence-mechanism Approach, Journal of Transportation Engineering, 129(4), 377-384.

Yang J., Jiang P., Suhail S. A., Sufian M., Deifalla A. F. (2023), Experimental Investigation and AI Prediction Modelling of Ceramic Waste Powder Concrete: An Approach Towards Sustainable Construction, Journal of Materials Research and Technology, 23, 3676-3696.

Yan X., Radwan E. (2006), Analyses of Rear-end Crashes Based on Classification Tree Models, Traffic Injury Prevention, 7(3), 276-282.

Yan X., Radwan E., Abdel-Aty M. (2005), Characteristics of Rear-end Accidents at Signalized Intersections using Multiple Logistic Regression Model, Accident Analysis and Prevention, 37(6), 983-995.

Yoo J. E. (2015), Random Forests, An Alternative Data Mining Technique to Decision Tree, Educational Evaluation Study, 28(2), 427-448.

Yuan R., Gu X., Peng Z., Xiang, Q. (2023), Analysis of Factors Affecting Occupant Injury Severity in Rear-end Crashes by Different Struck Vehicle Groups: A Random Thresholds Random Parameters Hierarchical Ordered Probit Model, Journal of Transportation Safety and Security, 15(6), 636-657.

Yuan Y., Wang S., Liu Z., Cui G., Wang Y. (2022), Influencing Factors Analysis of Side Right-angle Collisions Severity at Intersections Based on Decision Tree, International Journal of Crashworthiness, 27(1), 59-69.

Zhang W., Liu T., Yi J. (2022), Exploring the Spatiotemporal Characteristics and Causes of Rear-end Collisions on Urban Roadways, Sustainability, 14(18), 11761.