To precisely predict future data even when the number of pieces of time-series data is small, in predicting the future data, using the time-series data. When the future data is predicted using the time-series data, whether present time data is used is determined based on prediction variation or a data transition, and then the prediction of the future data is performed.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A prediction device comprising: a data acquisition unit configured to acquire present time data; a data generation unit configured to generate time-series data from the data acquired by the data acquisition unit at plurality of times; a determination unit configured to determine whether the generated time-series data satisfies a predetermined condition; and a final prediction unit configured to predict future data, based on past time data without using the present time data, when the predetermined condition is determined to be satisfied, and to predict the future data, based on the present time data and the past time data, when the predetermined condition is determined not to be satisfied, wherein past time data is previously acquired present time data which has been acquired prior to the present time data. 2. The prediction device according to claim 1, wherein, when the predetermined condition is determined not to be satisfied by the determination unit, the final prediction unit uses, as past time data, previously acquired present time data that falls within a predetermined range. 3. The prediction device according to claim 1, wherein the determination unit includes: a present time prediction unit configured to calculate a prediction result in a present time from the present time data and the past time data; and a comparison unit configured to determine whether the predetermined condition is satisfied, based on a first difference between the calculated prediction result in the present time and the prediction result in a past time calculated by the present time prediction unit in a past, and a second difference between the prediction results in past times calculated by the present time prediction unit in the past. 4. The prediction device according to claim 3, wherein the comparison unit determines that the predetermined condition is satisfied when the first difference is larger than the second difference. 5. The prediction device according to claim 3, wherein the comparison unit determines whether the predetermined condition is satisfied based on the first difference, and a statistic of a plurality of the second differences. 6. The prediction device according to claim 5, wherein the statistic is any of a maximum value, an average value, a median, and a most frequent value. 7. The prediction device according to claim 3, wherein the comparison unit determines whether the time-series data satisfies the predetermined condition, based on the first difference, and a transition of a plurality of the second differences. 8. The prediction device according to claim 1, wherein the determination unit includes: a detection unit configured to detect a transition of data similar to a transition of a part of the time-series data from past time-series data; and a transition determination unit configured to determine whether the predetermined condition is satisfied based on the detected similar transition of data. 9. The prediction device according to claim 1, wherein the determination unit includes: a detection unit configured to detect a transition of data similar to a transition of a part of the time-series data from time-series data of another machine number; and a transition determination unit configured to determine whether the predetermined condition is satisfied based on the detected similar transition of data. 10. The prediction device according to claim 8, wherein the detection unit detects a plurality of the similar transitions of data, and wherein the transition determination unit determines whether the predetermined condition is satisfied based on the plurality of similar transitions of data. 11. The prediction device according to claim 8, wherein the transition determination unit determines whether the predetermined condition is satisfied based on the plurality of weighted similar transitions of data. 12. The prediction device according to claim 1, wherein the future data is data about a degree of consumption, a degree of deterioration, or a possibility of occurrence of failure, of a component that configures a product. 13. A prediction method comprising: acquiring present time data; generating time-series data from the data acquired at a plurality of times; determining whether the generated time-series data satisfies a predetermined condition; and predicting future data, based on past time data without using the present time data, when the predetermined condition is determined to be satisfied, and predicting the future data, based on the present time data and the past time data, when the predetermined condition is determined not to be satisfied, wherein past time data is previously acquired present time data which has been acquired prior to the present time data. 14. A non-transitory computer-readable recording medium that stores a program for causing a computer to function as the units of a prediction device comprising: a data acquisition unit configured to acquire present time data; a data generation unit configured to generate time-series data from the data acquired by the data acquisition unit at plurality of times; a determination unit configured to determine whether the generated time-series data satisfies a predetermined condition; and a final prediction unit configured to predict future data, based on past time data without using the present time data, when the predetermined condition is determined to be satisfied, and to predict the future data, based on the present time data and the past time data, when the predetermined condition is determined not to be satisfied, wherein past time data is previously acquired present time data which has been acquired prior to the present time data.