Optimizing　the　AC　resistance　of　litz　wire　windings　is　crucial　for　reducing　loss　and　improving　the　efficiency　of　energy　transfer　in　power　systems.　This　study　presents　a　novel　method　for　obtaining　the　AC　resistance　of　litz　wire　windings　by　using　machine　learning　algorithms.　It　simplifies　and　improves　the　speed　at　which　AC　resistance　values　are　obtained　and　facilitates　the　study　of　AC　resistance　parameters　in　litz　wire　windings.　A　simulation　model　is　established　using　an　approximate　model　for　optimizing　the　AC　resistance　of　litz　wire　windings　based　on　the　Dowell　equation.　Maxwell　software　is　used　to　generate　the　training　dataset.　The　frequency,　dimensions,　number　of　layers,　and　conductivity　are　used　as　input　to　the　proposed　machine　learning　model,　while　the　AC　resistance　of　litz　wire　windings　is　the　output　variable.　A　neural　network　is　coupled　with　the　particle　swarm　optimization　method　to　optimize　the　network　structure　to　achieve　better　results.　The　proposed　machine　learning　model　has　a　prediction　accuracy　rate　of　99%.　　©　2024　IEEE.