Disclosed is a power network load factor prediction method based on intelligent algorithm optimization combination. According to the method, first of all, based on such means of Granger examination and the like, numerous factors related to load factors are screened and left under the condition that no information is omitted, and the analysis accuracy of the load factor-related factors and the predication precision of the load factors are guaranteed. When the load factors are predicted, such intelligent algorithms of an RBF nerve network, a GRNN nerve network, an SVR algorithm and the like are taken into consideration, the advantages of less omitted information, less attention to internal relations, high prediction precision and the like of an intelligent algorithm are brought into full play compared to a conventional prediction method, and multiple prediction results are optimized and combined by use of a genetic algorithm so as to further improve the prediction precision. The method provided by the invention can be used for load factor precision of different time scopes such as year, month, date and the like, can also be applied to the load factor prediction of such classified users as large industrial users, residential users and the like, and provides certain theoretical support for research correlated with a load factor price.