2026· International Conference on Conceptual Structures· pp. 373-387· 0 citations· 22 references
Computer Science
TL;DR
The findings suggest that the combination of fractional-order memory with physics-informed learning constitutes an effective and interpretable model for dengue forecasting, providing a sound model for epidemic forecasting.
Two variants of Echo State Networks (ESN) are introduced: Fractional ESN (fESN), which incorporates fractional-differencing dynamics into the reservoir to encode long-range dependence directly, and Wavelet ESN (wESN), which extracts stable low-frequency components through wavelet smoothing before modeling them with a m...
R. Goswami, Shinjini Paul, P. Ghosh et al.· arXiv.org· 0 citations
This study proposes a Fractional-Order Physics-Informed Neural Network (FPINN) framework for solving inverse parameter estimation problems in both fractional SIR and augmented SEIR epidemiological models and demonstrates that the proposed method accurately reconstructs epidemic trajectories and captures the influence o...
S. Naveen, V. Parthiban· Network Modeling Analysis in...· 0 citations
A loss-constrained time-varying parameter estimation neural network (L-TPENN), which directly incorporates the structural information of missing data into the objective loss function, enabling the model to handle the uncertainty caused by missing data during training.
Xiang-Lei Li, Jun Wang, Yue-Cai Han· Journal of Data and Dynamic...· 0 citations
A high-resolution forecasting framework that integrates daily dengue case data with meteorological drivers to improve predictions in Bangladesh and provides an efficient, reproducible, and scalable approach that can strengthen dengue preparedness in public health systems with limited resources is developed.
Mahadee Al Mobin, Arju Manara Begum· PLOS Global Public Health· 0 citations
A novel discrete fractional-order mathematical framework for modeling and forecasting the coupled progression of diabetes and cardiovascular complications, with emphasis on population dynamics in Saudi Arabia, offers valuable insights for public health decision-making and epidemic mitigation.
A. Elsonbaty, A. Aldurayhim, Waleed Adel· Journal of Nonlinear Mathema...· 0 citations
Empirical evidence is provided that it is vital to solve the leptokurtic distribution in infection data for obtaining stable forecasts and a new model called Robust Laplace-ARDL is proposed, which uses a Double Exponential (Laplace) distribution instead of the standard normal distribution to accommodate heavy-tailed di...
Gokul Thanigaivasan, Ratha Jeyalakshmi T, R. Mani et al.· Model Assisted Statistics an...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
