The invention discloses a training learning method and
system for a neural network of a paper pattern specification parameter
inference model. The method comprises the steps that S1, all connection weights and thresholds are subjected to initialization setting after multiple groups of learning samples are imported into an input layer; S2, one group of learning samples are selected randomly, and input and output of all units in an interlayer are calculated through an interlayer
algorithm; S3, output and response of all units of an output layer are calculated through an output layer
algorithm; S4, an output layer generalized error of all the units of the output layer is calculated, and an interlayer generalized error of all the units of the interlayer is calculated through an interlayer generalized error
algorithm; S5, the connection weight of the output layer is corrected, the output threshold of the output layer is corrected through a
correction algorithm, the connection weight of the interlayer is corrected, and the output threshold of the interlayer is corrected through the
correction algorithm; and S6, the next group of learning samples are selected randomly, and the step S2 is returned to. According to the training learning method and
system, a network is converged step by step through selection of a proper training rate and other methods, and therefore the training learning effect is improved.