| Popis: |
Efficient and scalable implementations of parallel genetic algorithms (PGAs) have been devised for an affordable MIMD parallel processing system. PGAs with structured populations have been compared with traditional genetic algorithms and found to give superior search performance. The parallel processing system constructed has enabled empirical research into the evolutionary approach to constructing problem-specific artificial neural networks (ANNs). This work, involving a real world speech recognition problem, has shown that a high level parametric description of ANNs is an effective method of encoding their properties in a form suitable for manipulation by genetic algorithms. |
