基于人工神经网络的技术生命周期 测度方法研究

An Artificial Neural Network Method for Technology Life Cycle Measurement

对技术生命周期进行研究可以了解技术的发展历史和趋势,在技术交易、技术预测和技术评价等领域有较大的价值;也是企业战略制定,政府政策制定等的重要参考依据。以专利数据为基础,运用数理统计的方法可以拟合出技术的生命周期曲线。本文建立了一种基于人工神经网技术的技术生命周期测度方法,并以高温气冷堆技术为例进行测算。将测算结果与使用Logistic回归方法得到的结果进行比较。结果表明:人工神经网络方法在拟合和预测效果上都表现更优。

Research of technology life cycle(TLC)could find out the development history and trend of technology,which is very valuable in technology transaction,technology prediction,technology evaluation and other fields.It is also an important reference basis for enterprise strategy making and government policy making.The TLC-curve could be fit by mathematical statistics method based on patent data.A new method based on artificial neural network was constructed in this paper for TLC measurement,and it took the high-temperature gas-cooled reactor technology as a sample.The measurement results were compared with the results using Logistic regression method.The results found that the artificial neural network method performed better in the fitting and prediction effect than the common Logistic regression method.