| 基于E-BP神经网络的科技奖励评价模型研究 |
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| 引用本文： | 王瑛,赵谦,曹玮. 基于E-BP神经网络的科技奖励评价模型研究[J]. 科技进步与对策, 2011, 28(10): 111-114. DOI: 10.3969/j.issn.1001-7348.2011.10.027 |
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| 作者姓名： | 王瑛 赵谦 曹玮 |
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| 作者单位： | 湖南大学金融与统计学院;湖南大学经济与贸易学院; |
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| 基金项目： | 湖南省自然科学基金项目 |
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| 摘 要： | 根据简单多数原则引入专家动态权数,与人工神经网络BP算法相结合,构建E-BP科技奖励综合评价智能模型。实证分析表明,该模型减少了传统科技奖励评价方法中受专家主观因素和模糊随机因素的影响,使评价结果更加客观、合理。
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| 关 键 词： | 专家动态权数 E-BP神经网络模型 科技奖励 综合评价 |
Based on E-BP Neural Network Model for Intelligent Evaluation of Science and Technology Award |
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| Wang Ying,Zhao Qian,Cao Wei. Based on E-BP Neural Network Model for Intelligent Evaluation of Science and Technology Award[J]. Science & Technology Progress and Policy, 2011, 28(10): 111-114. DOI: 10.3969/j.issn.1001-7348.2011.10.027 |
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| Authors: | Wang Ying Zhao Qian Cao Wei |
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| Affiliation: | Wang Ying1,Zhao Qian1,Cao Wei2 (1.College of Finance and Statistics,Hunan University,Changsha 410079,China,2.College of Economy and Trade,China) |
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| Abstract: | According to the principle of simple majority, the introduction of dynamic experts weight and artificial neural network BP algorithm for combining E-BP model to build a comprehensive evaluation of intelligent model of Science and Technology Award. Empirical analysis shows that the model to reduce the traditional methods of science and technology award by the expert's subjective evaluation factors and fuzzy stochastic factors, therefore, the results to be more objective and reasonable. |
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| Keywords: | Dynamic Experts' Weight E-Bp Neural Network Model Science and Technology Award Comprehensive Evaluation |
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