Author:
Das Monidipa,Ghosh Soumya K.
Publisher
Springer International Publishing
Reference16 articles.
1. Das, M., Ghosh, S.K.: A probabilistic approach for weather forecast using spatio-temporal inter-relationships among climate variables. In: 2014 9th International Conference on Industrial and Information Systems (ICIIS), pp. 1–6. IEEE (2014)
2. Das, M., Ghosh, S.K.: BESTED: An exponentially smoothed spatial Bayesian analysis model for spatio-temporal prediction of daily precipitation. In: Proceedings of the 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, p. 55. ACM (2017)
3. Das, M., Ghosh, S.K.: semBnet: a semantic Bayesian network for multivariate prediction of meteorological time series data. Pattern Recognit. Lett. 93, 192–201 (2017)
4. Das, M., Ghosh, S.K.: Spatio-temporal prediction of meteorological time series data: an approach based on spatial Bayesian network (SpaBN). In: International Conference on Pattern Recognition and Machine Intelligence, pp. 615–622. Springer, Berlin (2017)
5. Das, M., Ghosh, S.K.: Spatio-temporal prediction under scarcity of influencing variables: a hybrid probabilistic graph-based approach. In: 2017 Ninth International Conference on Advances in Pattern Recognition (ICAPR), pp. 1–6. IEEE (2017)