基于GA-BP神经网络的专利技术产业化全过程评价研究

Evaluation on the Whole Process of Patent Industrialization Based on GA-BP Neural Network

从系统流程的角度界定和分析专利技术产业化所需经历的阶段,并根据每个阶段的特点作出合理的评价,是实现专利技术顺利转化的基础,鉴此对专利技术产业化全过程进行了定义,认为其包含新产品开发、市场化和规模化生产3个阶段,藉此建立专利技术产业化全过程的评价指标体系,运用遗传算法改进的BP神经网络建立专利技术产业化全过程评价模型,以调研所得数据对网络进行训练,用训练好的网络对专利技术产业化全过程进行评估,结果表明该模型具有较好的可行性和实用性。

Defining and analyzing the each stage which the whole process of patent industrialization from the view of systematic process needed to experience,and making a fair assessment in accordance with the characteristics of each stage,are the basis of achieving a smooth transformation of patent.So this paper firstly defines the whole process of patent industrialization,which contains three stages：new product development stage,the market-oriented phase and large-scale production phase,electing indicators of the whole process of patent industrialization,and then based on the BP neural network of Genetic Algorithm（GA）to build the model of the whole process of patent industrialization,and using the collective data to do the network training,finally using trained network to do the evaluation of the whole process of patent industrialization,the answer proves that this model has good feasibility and practicality.