Genetic and Bacterial Programming for B-Spline Neural Networks Design
János Botzheim*, Cristiano Cabrita**, László T. Kóczy*,***,
and Antonio E. Ruano**
*Department of Telecommunications and Media Informatics, Budapest University of Technology and Economics, Magyar Tudósok Krt. 2, Budapest, H-1117, Hungary
**Centre for Intelligent Systems, University of Algarve, Campus de Gambelas, 8000 Faro, Portugal
***Institute of Information Technology and Electrical Engineering, Széchenyi István University, Győr, Hungary
The design phase of B-spline neural networks is a highly computationally complex task. Existent heuristics have been found to be highly dependent on the initial conditions employed. Increasing interest in biologically inspired learning algorithms for control techniques such as Artificial Neural Networks and Fuzzy Systems is in progress. In this paper, the Bacterial Programming approach is presented, which is based on the replication of the microbial evolution phenomenon. This technique produces an efficient topology search, obtaining additionally more consistent solutions.
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