Percolative Behavior Models Based on Artificial Neural Networks for Electrical Percolation of AOT Microemulsions in the Presence of Crown Ethers as Additives

2014 ◽  
Vol 51 (6) ◽  
pp. 533-540 ◽  
Author(s):  
Óscar Moldes ◽  
Antonio Cid ◽  
Gonzalo Astray ◽  
Juan Mejuto
2020 ◽  
Vol 5 ◽  
Author(s):  
Peter Kielar ◽  
André Borrmann

Movement behavior models of pedestrian agents form the basis of computational crowd simulations. In contemporary research, a large number of models exist. However, there is still no walking behavior model that can address the various influence factors of movement behavior holistically. Thus, we endorse the use of artificial neural networks to develop walking behavior models because machine learning methods can integrate behavioral factors efficiently, automatically, and data-driven. In this paper, we support this approach by providing a framework that describes how to include artificial neural networks into a pedestrian research context. The framework comprises 5 phases: data, replay, training, simulation, and validation. Furthermore, we describe and discuss a prototype of the framework.


2012 ◽  
Vol 49 (4) ◽  
pp. 316-320 ◽  
Author(s):  
Iago Antonio Montoya ◽  
Gonzalo Astray ◽  
Antonio Cid ◽  
José Antonio Manso ◽  
Oscar Adrían Moldes ◽  
...  

2015 ◽  
Vol 52 (6) ◽  
pp. 473-476 ◽  
Author(s):  
Iago Antonio Montoya ◽  
Oscar Adrían Moldes ◽  
Antonio Cid ◽  
Gonzalo Astray ◽  
Juan Francisco Gálvez ◽  
...  

Author(s):  
Kobiljon Kh. Zoidov ◽  
◽  
Svetlana V. Ponomareva ◽  
Daniel I. Serebryansky ◽  
◽  
...  

Sign in / Sign up

Export Citation Format

Share Document