id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-321913-zie2uv21	Godio, Alberto	SEIR Modeling of the Italian Epidemic of SARS-CoV-2 Using Computational Swarm Intelligence	2020-05-18		.txt	text/plain	8247	394	55	We focused on the application of a stochastic approach in fitting the model parameters using a Particle Swarm Optimization (PSO) solver, to improve the reliability of predictions in the medium term (30 days). We present an updated version of the predictive model of epidemic phenomena based on the approach called SEIR (Susceptible-Exposed-Infective-Recovered), widely used to analyze infection data during the different stages of an epidemic outbreak. Figure 5a ,b shows the SEIR model prediction for the Veneto region, according to the deterministic and PSO approaches, respectively. Figure 5a ,b shows the SEIR model prediction for the Veneto region, according to the deterministic and PSO approaches, respectively. The SEIR modeling for the Piedmont region is shown in Figure 6a ,b, where the solution using the deterministic and PSO prediction are reported, respectively. The SEIR modeling for the Piedmont region is shown in Figure 6a ,b, where the solution using the deterministic and PSO prediction are reported, respectively.	./cache/cord-321913-zie2uv21.txt	./txt/cord-321913-zie2uv21.txt