Case-Based Reasoning in identifying causes of fish death in industrial fish farming
Fish farming is a million dollar business world wide, and fish is in fact the third most
important export product after oil/gas and metal in Norway. There are a lot of different aquaculture sites which produce fish along our long coast line and they all have some
differences in the production rates and procedures. The fish farmer at these sites hold
valuable information about the production, which is almost impossible to derive only
from empirical data.
In this thesis we introduce Glaucus, a Case-Based Reasoning system which aims to
help the fish farmers with their decision making when conduction sorting operations at
their aquaculture sites. The system is built in Java and uses the jColibri development
framework for Case-Based Reasoning. It retrieves cases based on similarity function from
myCBR and jColibri in addition to custom made ones. The case base is generated from
real world data and the case queries are populated by a combination of user input and
data from a database with continuous data flow.
Our approach is just the beginning of what we hope will be a even greater journey
towards a complete decision support system that will meet the expectations of the fish
Keywords: Case-Based Reasoning, Machine learning, Fish farming, jColibri, myCBR
Place, publisher, year, edition, pages
Institutt for datateknikk og informasjonsvitenskap , 2011. , 177 p.
ntnudaim:6118, MTDT datateknikk, Intelligente systemer
IdentifiersURN: urn:nbn:no:ntnu:diva-15401Local ID: ntnudaim:6118OAI: oai:DiVA.org:ntnu-15401DiVA: diva2:489216
Aamodt, Agnar, ProfessorTidemann, Axel