Dr. Dipankar Das

1. Das, D. (2025). Soft Computing-Based Ensemble Technique for WPI Estimation in India’s Textile Sector. International Research Journal of Multidisciplinary Scope, 6(3). DOI https://doi.org/ 10.47857/irjms.2025.v06i03.04681 2. Das, D., & Mukhopadhyay, S. (2025). Comparative analysis of automatic time-series forecasting approaches for potato wholesale price index in India. International Journal of Computational Economics and Econometrics, 15(3). DOI https://dx.doi.org/10.1504/IJCEE.2025.147776 3. Das, D., & Chakrabarti, S. (2023). An Extreme Learning Machine Approach for Forecasting the Wholesale Price Index of Food Products in India. Pertanika Journal of Science & Technology, 31(6). DOI https://doi.org/10.47836/pjst.31.6.30 4. Chakraborty, A., Das, D., Mitra, S., De, D., & Pal, A. J. (2022). Forecasting adversities of COVID- 19 waves in India using intelligent computing. Innovations in Systems and Software Engineering, 1-17. DOI https://doi.org/10.1007/s11334-022-00486-y 5. Das, D., & Chakrabarti, S. (2022). Forecasting non-linear macroeconomic indexes of India: an ensemble of MLP and Holt’s linear methods. International Journal of Advanced Technology and Engineering Exploration, 9(93), 1134. DOI http://dx.doi.org/10.19101/IJATEE.2021.875707 6. Das, D., & Chakrabarti, S. (2022). Forecasting of the WPI of Textiles in India: An Neural Approach. In: Mandal, J.K., De, D. (eds) Advanced Techniques for IoT Applications. EAIT 2021. Lecture Notes in Networks and Systems, 292. Springer, Singapore. DOI https://doi.org/10. 1007/978-981-16-4435-1_15 7. Chakraborty, A., Mitra, S., Das, D., De, D., & Pal, A. J. (2022). Forecasting COVID-19 outbreak in India using time series dataset: an ensemble of ARIMA, Abbasov-Mamedova, and multilayer perceptron models. In: Mandal, J.K., De, D. (eds) Advanced Techniques for IoT Applications. EAIT 2021. Lecture Notes in Networks and Systems. 292. Springer, Singapore. DOI https://doi.org/10.1007/978-981-16-4435-1_17 8. Chakraborty, A., Mitra, S., Das, D., Battacharyya, D., De, D., Mondal, S. P., & Pal, A. J. (2022). Active learning-based estimation of COVID-19 pandemic: a synergetic case study in selective regions population. In: Garg, L., Chakraborty, C., Mahmoudi, S., Sohmen, V.S. (eds) Healthcare Informatics for Fighting COVID-19 and Future Epidemics. EAI/Springer Innovations in Communication and Computing. Springer, Cham. DOI https://doi.org/10.1007/978-3-030-72752-9_ 3 9. Das, D., & Chakrabarti, S. (2021). Forecasting non-linear WPI of manufacture of chemicals and chemical products in India: an MLP approach. International Journal of Advanced Technology and Engineering Exploration, 8(82), 1193. DOI http://dx.doi.org/10.19101/IJATEE.2021.874407 10. Chakraborty, A., Mitra, S., Das, D., De, D., & Pal, A. J. (2021). Fuzzy Time Series Forecasting of COVID-2019 Outbreak: A Case Study of US Population. In: Balas, V.E., Hassanien, A.E., Chakrabarti, S., Mandal, L. (eds) Proceedings of International Conference on Computational Intelligence, Data Science and Cloud Computing. Lecture Notes on Data Engineering and Communications Technologies. 62. Springer, Singapore. DOI https://doi.org/10.1007/978-981-33-4968-1_ 5 11. Das, D., & Chakrabarti, S. (2021). Forecast model development of some selected wholesale price index of India using MLP. In: Balas, V.E., Hassanien, A.E., Chakrabarti, S., Mandal, L. (eds) Proceedings of International Conference on Computational Intelligence, Data Science and Cloud Computing. Lecture Notes on Data Engineering and Communications Technologies. 62. Springer, Singapore. DOI https://doi.org/10.1007/978-981-33-4968-1_18