Journals (24)

Citations: 1480 h-index: 22 i10-index: 36

Publication Summary

ABDC: A*- 1 + A- 12+ B- 2

SCI/SCIE/SSCI/Scopus: 24

2024 (1)

Sarkar, S., Paramanik, A. R., & Mahanty, B. (2024). A Z-Number Slacks-Based Measure DEA model-based Framework for Sustainable Supplier Selection with Imprecise Information. Journal of Cleaner Production, 436, 140563. - (Link: Paper) (ABDC: A)

Pramanik, A., Sarkar, S., & Pal, S. K. (2023). Video surveillance-based fall detection system using object-level feature thresholding and Z-numbers. Knowledge-Based Systems, 280, 110992.- (Link: Paper) (ABDC: A)
Bag, S., Golder, R., Sarkar, S., & Maity, S. (2023). SENE: A Novel Manifold Learning Approach for Distracted Driving Analysis with Spatio-Temporal and Driver Praxeological Features. Engineering Applications of Artificial Intelligence, 123, Part C, 106332. (Link: Paper)
Bhattacharyya, S., Sarkar, S., Sarkar, B., & Manatkar, R. (2023). Risk modeling framework for strategic and operational intervention to enhance the effectiveness of a closed-loop supply chain. IEEE Transactions on Engineering Management, 71, 7015-7028. (Link: Paper)- (ABDC: A)
Dey, P., Chowdhury, S., Abadie, A.,Vann Yaroson, E., & Sarkar, S. (2023). Artificial intelligence-driven supply chain resilience in Vietnamese manufacturing small- and medium-sized enterprises. International Journal of Production Research. (Link: Paper)- (ABDC: A)
Paramanik, A. R., Sarkar, S., & Sarkar, B. (2023). A Two-stage Improved Base Point Slacks-Based Measure of Super-efficiency for Negative Data Handling. Computers & Operations Research, 150, 106057. (Link: Paper)- (ABDC: A)
Sarkar, S., Pramanik, A., & Maiti, J. (2023). An Integrated Approach using Rough Set Theory, ANFIS, and Z-number in Occupational Risk Prediction. Engineering Applications of Artificial Intelligence, 117, Part A, 105515. (Link: Paper).

Das, S., & Sarkar, S. (2022). News media mining to explore speed-crash-traffic association during COVID-19. Transportation Research Record. (Link: Paper). (ABDC: B)
Das, S., Eun, P., & Sarkar, S. (2022). Impact of operating speed measures on traffic crashes: Annual and daily level models for rural two-lane and rural multilane roadways. Journal of Transportation Safety & Security, 15(6), 584-603. (Link: Paper).
Paramanik, A. R., Sarkar, S., & Sarkar, B. (2022). OSWMI: An Objective-Subjective Weighted method for Minimizing Inconsistency in multi-criteria decision making. Computers & Industrial Engineering, 169, 108138. (Link: Paper). (ABDC: A)
Riccardi, M.R., Mauriello, F., Sarkar, S., Galante, F., Scarano, A., & Montella, A. (2022). Parametric and Non-Parametric Analyses for Pedestrian Crash Severity Prediction in Great Britain. Sustainability, 14(6), 3188.- (Link: Paper).
Sarkar, S., Ejaz, N., Maiti, J. & Pramanik, A. (2022). An integrated approach using growing self-organizing map-based genetic K-means clustering and tolerance rough set in occupational risk analysis. Neural Computing & Applications, 34, 9661-9687. - (Link: Paper).
Sarkar, S., Vinay, S., Djeddi, C., & Maiti, J. (2022). Classification and pattern extraction of incidents: A deep learning-based approach. Neural Computing & Applications, 34, 14253–14274. - (Link: Paper)

Sarkar, S., Pramanik, A., Maiti, J., & Reniers, G. (2021). COVID-19 Outbreak: A Data-driven Optimization Model for Allocation of Patients. Computers & Industrial Engineering, 161, 107675. (Link: Paper). [Included in the World Health Organization (WHO) database (Link)] (ABDC: A)
Pramanik, A., Sarkar, S., & Maiti, J. (2021). A real-time video surveillance system for traffic pre-events detection. Accident Analysis & Prevention, 154, 106019. (Link: Paper) (ABDC: A*)
Pramanik, A., Sarkar, S., Maiti, J., & Mitra, P. (2021). RT-GSOM: Rough tolerance growing self-organizing map. Information Sciences, 566, 19-37. (Link: Paper)

Sarkar, S., & Maiti, J. (2020). Machine learning in occupational accident analysis: A review using science mapping approach with citation network analysis. Safety Science, 131, 104900. (Link: Paper) (ABDC: A)
Sarkar, S., Pramanik, A., Maiti, J., & Reniers, G. (2020). Predicting and analyzing injury severity: A machine learning-based approach using class-imbalanced proactive and reactive data. Safety Science, 125, 104616. (Link: Paper) (ABDC: A)

Sarkar, S., Raj, R., Vinay, S., Maiti, J., & Pratihar, D. K. (2019). An optimization-based decision tree approach for predicting slip-trip-fall accidents at work. Safety Science, 118, 57-69. (Link: Paper) (ABDC: A)
Sarkar, S., Vinay, S., Raj, R., Maiti, J., & Mitra, P. (2019). Application of optimized machine learning techniques for prediction of occupational accidents. Computers & Operations Research, 106, 210-224. (Link: Paper) (ABDC: A)

Sarkar, S., Pratihar, D. K., & Sarkar, B. (2018). An integrated fuzzy multiple criteria supplier selection approach and its application in a welding company. Journal of manufacturing systems, 46, 163-178. (Link: Paper) (ABDC: B)

Gautam, S., Maiti, J., Syamsundar, A., & Sarkar, S. (2017). Segmented point process models for work system safety analysis. Safety Science, 95, 15-27. (Link: Paper) (ABDC: A)
Singh, K., Raj, N., Sahu, S. K., Behera, R. K., Sarkar, S., & Maiti, J. (2017). Modelling safety of gantry crane operations using petri nets. International journal of injury control and safety promotion, 24(1), 32-43. (Link: Paper)

Krishna, O. B., Maiti, J., Ray, P. K., Samanta, B., Mandal, S., & Sarkar, S. (2015). Measurement and modeling of job stress of electric overhead traveling crane operators. Safety and health at work, 6(4), 279-288. (Link: Paper)