In order to select factors closely related to the prediction and representative samples, the factors and samples are optimized using PPR and B P neural network respectively.

• 为了选择与预报量有密切关系的因子和有代表性的样本，分别采用投影寻踪回归（PPR）和B?P神经网络对因子和样本进行优选。