Title :
Neural network approach in failure characteristic analysis associated with boom containment
Author_Institution :
Dept. of Electr. & Comput. Eng., Miami Univ., Coral Gables, FL
fDate :
27 Jun-2 Jul 1994
Abstract :
The use of boom structures has been recognized as an efficient method for cleaning up oil spills; however, non-Newtonian characteristic involved in high-viscosity oils results in obstacle to any theoretical boom containment analysis. This paper addresses a neural network approach for failure characteristic analysis associated with boom containment of high-viscosity oils
Keywords :
environmental science computing; failure analysis; neural nets; water pollution control; boom containment; failure characteristic analysis; high-viscosity oils; non-Newtonian characteristic; oil spill cleaning; water pollution; Backpropagation; Character recognition; Cleaning; Equations; Failure analysis; Intelligent networks; Internal stresses; Neural networks; Petroleum; Viscosity;
Conference_Titel :
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-1901-X
DOI :
10.1109/ICNN.1994.374768
