| 摘要 |
PURPOSE: To more exactly predict a large fluctuation by learning a learning set corresponding to the large fluctuation emphatically. CONSTITUTION: A learning control means 200 is provided with a comparing means 220 for comparing the absolute value of a teacher signal with a prescribed value, learning means 210 for performing learning prescribed times with the first learning set when the absolute value of the teacher signal is larger in the comparison of the comparing means 220, and learning stop means 250 for stopping the learning of the learning means 210 when the performance of large fluctuation prediction gets maximum. Thus, a learning set L is first selected so that the absolute value in the change of time of predictive object time sequential data can be larger than the prescribed value and next, the learning set L is learnt by increasing the number of times to present it to a neural network in comparison with any learning set excepting for the learning set L. Thus, the learning set corresponding to the large fluctuation can be learnt emphatically rather than learning equally presenting all the learning sets, and the large fluctuation can be more exactly predicted. |
