PURPOSE: To effectively realize the prediction of time sequence data and the recognition of the prediction result even when an object generating the time sequence data cannot be theoreically analized and cannot be expressed with an expression by the time sequence data.

CONSTITUTION: The data in an arbitrary time zone of preliminarily prepared time sequence data for learning are inputted in a neural network 1 consisting of a plurality of neurons and the network is made to learn so that the time sequence data of a prescribed time after can be outputted. data for each time unit by means of the neural network 1, a prediction value for a prescribed time unit after can be obtained. By separately providing another neural network 4 for recognition and inputting the prediction value from the neural network 1 and the time sequence data, the prediction of the time sequence data can be recognized.