Evaluation　and　prediction　of　power　network　system　robustness　are　conducive　to　system　managers＇　ability　to　perceive　the　current　status　of　network　system　operations　and　take　timely　measures　to　cope　with　potential　risks.　Therefore,　a　robustness　prediction　model　for　power　dispatching　data　network　is　proposed　based　on　an　improved　whale　optimization　algorithm.　Firstly,　an　evaluation　index　system　for　the　robustness　of　the　power　dispatching　data　network　is　constructed　and　data　dimensionality　reduction　processing　is　designed　based　on　methods　such　as　field　extraction　and　formula　mapping.　Moreover,　an　improved　chaotic　mapping　and　adaptive　weight-whale　optimization　algorithm(CA-WOA-BP)is　proposed　based　on　chaotic　mapping　and　adaptive　weights(WOA-BP)and　a　power　network　robustness　prediction　method　is　established.　Experimental　results　show　that　compared　with　the　WOA-BP　algorithm,　the　proposed　improved　algorithm　speeds　up　the　convergence　of　the　prediction　model　while　overcoming　the　situation　of　falling　into　local　optima　and　reduces　the　absolute　error　percentage　of　the　predicted　values　by　5.　3　%,　which　helps　users　to　discover　the　robustness　of　power　dispatching　data　network　systems　more　accurately　and　timely.　©　2025　Editorial　Department　of　Southern　Power　System　Technology.　All　rights　reserved.