New algorithm swiftly escapes local minima, reaching global minima efficiently.
A new back-propagation algorithm was developed to escape local minima and reach global minima faster than the standard Back-Propagation algorithm. By using a modified error function and XOR, the algorithm was able to achieve this goal successfully. The results show that the new algorithm can quickly escape local minima and converge to global minima, meeting expectations.
