Title :
An artificial neural network for oil spill cleanup: the MUSE system
Author_Institution :
Performace Support Syst. Group, Centre for Inf. Technol. Innovation, Laval, Que.
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;
Conference_Titel :
Electrical and Computer Engineering, 1995. Canadian Conference on
Conference_Location :
Montreal, Que.
Print_ISBN :
0-7803-2766-7
DOI :
10.1109/CCECE.1995.528188
