Aiming at combination forecasting problems of describing uncertainty by interval numbers, in order to improve the forecasting accuracy of interval data, firstly, the induced ordered weighted continuous generalized ordered weighted averaging (IOWC-GOWA) operator is used to aggregate the interval numbers into real numbers, then we normalize them. Finally, by introducing relative entropy as the optimum criterion from the perspective of information theory, an interval combination forecasting model based on IOWC-GOWA operator and relative entropy is proposed. Furthermore, the rationality and effectiveness of the combined forecasting model is analyzed by an example. The results show that the combination forecasting model can effectively improve the forecasting accuracy of interval data. That is to say，the model is reasonable and effective. Additionally, the selection of the parameter λand the BUM function has a certain impact on the prediction accuracy of the model.