Artificial intelligence knacks-based computing for stochastic COVID-19 SIRC epidemic model with time delay

• DOI: 10.1142/s0217979222501740
• Publication Date: 2022-08-16T15:48:58Z
• Authors: Muhammad Shoaib; Adeeba Haider; Muhammad Asif Zah...; Kottakkaran Soopp...
• Keywords: Basic reproduction number

Time delays play an important part in modeling the fact that one cannot be communicable for a long time after becoming sick. Delay can triggered by variety of epidemiological situations. The most egregious causes delay are infection latency vector and infected host. dynamics susceptible, infected, recovered cross-immune (SIRC) classed-based model having time-delay transmission spread COVID-19 abbreviated as (SIRC-CTC-19) investigated this study using intelligent numerical computing paradigm based on Levenberg–Marquardt Method backpropagated neural networks (LM-BPNN). is mathematically governed system ordinary differential equations depicts four nodes ones with class components dissemination (CTC-19). reference solution SIRC produced explicit Runge–Kutta method many scenarios arising from altering regard to time. This permits use evolutionary solve SIRC-CTC-19 train, validate test techniques. proposed LM-BPNN method’s accuracy has been proven its results overlapping Calculation regression metrics, error analysis histogram illustrations learning curves MSE effectively augment LM-BPNN’s accuracy, convergence reliability solving model.