Figures index

From

Analytical Comparison of Swarm Intelligence Optimization versus Behavioral Learning Concepts Adopted by Neural Networks (An Overview)

Hassan M. H. Mustafa

American Journal of Educational Research. 2015, 3(7), 800-806 doi:10.12691/education-3-7-2
  • Figure 1. Block diagram of generalized ANN modeling for supervised and unsupervised paradigms, adapted from [22]
  • Figure 2. Illustrates the comparison between Pavlovian and Thorndikian work. The comparison considers normalized results after application of ANN simulation adapted from [3]
  • Figure 3. The dashed line indicate the approach to Cramer-Rao bound based on Fisher information adapted from [23]
  • Figure 4. Graphical presentation for learning performance under noisy conditions with reference to Table 1 adapted from [12]
  • Figure 5. Illustrates the average (of statistical distribution) for learning response time (number of iteration cycles) for different learning rate values (eta)
  • Figure 6. Illustrates graphical presentation for reach optimal solution of TSP under noisy conditions by referring to Table 2
  • Figure 7. Cooperating ants find better solutions in a shorter time, on the average 25 runs. The number of ants was set to m=4, adapted from [27]
  • Figure 8. Illustrates decay curve for misclassification error value versus the increase of generation in parallel genetic algorithm (for some constant population size) adapted from [17]
  • Figure 9. Idealized learning curve of the LMS algorithm adapted from [22]
  • Figure 10. Obtained ordered eigenvalues of data set randomized vectors adapted from [26]