An artificial neural network for oil spill cleanup: the MUSE system

Author

Arcand, J.-F.

Author_Institution

Performace Support Syst. Group, Centre for Inf. Technol. Innovation, Laval, Que.

Volume

1

fYear

1995

Firstpage

519

Abstract

An extensive and comprehensive shoreline cleanup knowledge-base was developed as part of the implementation of a decision support system for teams involved in oil spill cleanup operations. The system, ShoreClean, was designed to provide environmental emergency response teams with a decision support system that would allow them to improve their efficiency. It was implemented with a backward chaining rule-based system. An expert system was a judicious choice for the development of the system´s knowledge base, but the constant updating of the knowledge-base and the incapacity of the system to respond to fuzzy questioning caused the author to migrate toward a distributed artificial neural network (DANN). This article describes the grafting of the rule-based system and DANN

Keywords

backward chaining; decision support systems; disasters; expert systems; neural nets; problem solving; water pollution; MUSE system; backward chaining rule-based system; decision support system; distributed artificial neural network; environmental emergency response teams; fuzzy questioning; oil spill cleanup; shoreline cleanup knowledge-base; Artificial neural networks; Decision support systems; Expert systems; Fuzzy neural networks; Fuzzy systems; Hybrid intelligent systems; Information technology; Knowledge based systems; Neurons; Petroleum;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical and Computer Engineering, 1995. Canadian Conference on

Conference_Location

Montreal, Que.

ISSN

0840-7789

Print_ISBN

0-7803-2766-7

Type

conf

DOI

10.1109/CCECE.1995.528188

Filename

528188