Abstract
The research on technology life cycle can be used in technology transaction, technology prediction, technology evaluation and so on. It is an important reference basis for enterprise strategy making, government policy making and so on. This study constructed a BP neural network model based on the patent accumulative quantity to judge the TLC, and compares the results with the logistics regression method which is the more mature in academic circles. It is found that it is feasible to use BP neural network to study TLC with a better result on technology prediction and no difference in identifying TLC phase compared to logistics regression.
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