Abstract: This paper shows the performance of artificial intelligence mainly associated with the swarm intelligence concept to find minima and maxima of a set of benchmark functions. The implementation is basically carried to optimize Neural Networks using swarm intelligence to overcome the effect of training algorithms (Back propagation) which get stuck at local minima or local maxima in many applications, using swarm intelligence. This is a part of research work which is carried to show the performance of above algorithms in finding the maxima/minima of the benchmark functions.. The results shows that these swarm concepts have no tendency to get stuck at local minima or local maxima and proper parameter selection to these algorithms produces excellent results.
Keywords: Ant colony optimization, Artificial. Intelligence, Evolutionary algorithms, Genetic Algorithm, Particle swarm optimization.
|
DOI:
10.17148/IJARCCE.2022.11796
