Name
Title | ||
|---|---|---|
Combined fuzzy logic and genetic algorithm techniques-application to an electromagnetic field problem |
Abstract | ||
|---|---|---|
The influence of a faulted electrical power transmission line on a buried pipeline is investigated. The induced electromagnetic field depends on several parameters, such as the position of the phase conductors, the currents flowing through conducting materials, and the earth resistivity. A fuzzy logic system was used to simulate the problem. It was trained using data derived from finite element method calculations for different configuration cases (training set) of the above electromagnetic field problem. After the training, the system was tested for several configuration cases, differing significantly from the training cases, with satisfactory results. It is shown that the proposed method is very time efficient and accurate in calculating electromagnetic fields compared to the time straining finite element method. In order to create the rule base for the fuzzy logic system a special incremental learning scheme is used during the training. The system is trained using genetic algorithms. Binary and real genetic encoding were implemented and compared. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1016/S0165-0114(01)00137-3 | Fuzzy Sets and Systems |
Keywords | Field | DocType |
fuzzy modeling,finite element method calculation,finite element method,induced electromagnetic field,inductive interference,genetic algorithms,configuration case,genetic algorithm techniques-application,training set,fuzzy logic,fuzzy logic system,electromagnetic field,training case,electromagnetic field problem,combined fuzzy logic,genetics,rule based,electric power,genetic algorithm,transmission line | Transmission line,Fuzzy logic,Algorithm,Finite element method,Artificial intelligence,Fuzzy control system,Membership function,Electromagnetic field,Machine learning,Genetic algorithm,Mathematics,Binary number | Journal |
Volume | Issue | ISSN |
129 | 3 | Fuzzy Sets and Systems |
Citations | PageRank | References |
6 | 0.87 | 9 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| I. G. Damousis | 1 | 90 | 7.09 |
| K. J. Satsios | 2 | 6 | 0.87 |
| D. P. Labridis | 3 | 6 | 0.87 |
| P. S. Dokopoulos | 4 | 6 | 0.87 |