NP2.3Artificial Intelligence, Cognitive models and Data Inversion In Geosciences
|Convener: Sid-Ali Ouadfeul | Co-Convener: Leila Aliouane
/ Attendance Tue, 09 Apr, 17:30–19:00 / Blue Posters
A cognitive model is an approximation to human cognitive processes for the purposes of comprehension and prediction. Cognitive models can be developed within or without a cognitive architecture. Cognitive modeling historically developed within cognitive psychology which is a cognitive science that include human factors. It and has received contributions from the fields of machine learning and artificial intelligence. There are many types of cognitive models, and they can range from box-and-arrow diagrams to a set of equations to software programs that interact with the same tools that humans use to complete tasks.
Artificial intelligence (AI) involves the study of cognitive phenomena in machines; it has been widely used in geosciences. Artificial Neural Networks (ANNs) and Fuzzy Logic are two kinds of cognitive models used in many field of the earth sciences.
The goal of this session is to show the utility of cognitive models and artificial intelligence in all branches of geosciences.
The session is also devoted on data inversion in geosciences.
New researches and case studies related to cognitive models are welcome.
Selected papers will be published in a special issue of the peer reviewed journal "Pattern Recognition in Physics http://www.pattern-recognition-in-physics.net/home.html