摘 要: 为了对高校科研项目前景进行有效预测,进一步提升科研成果转化率,本文提出了基于神经网络结合科研项目共享的网络平台,构建可靠的科研项目前景预测系统。通过将各类大量科研项目的特征参数化,利用BP(反向传播)神经网络的非线性映射能力、自适应能力和对离散数据的泛化能力生成模型后,用于从多维度对一个新项目生成可靠的前景预测。实验表明,BP神经网络算法在大量学习经过预处理的样本后所产生的预测结果是具有较高准确性的,且能够随着新的样本输入不断更新和适应,因此该方法具有较强的可行性。 |
关键词: 高校科研项目;前景预测;神经网络 |
中图分类号: TP183
文献标识码: A
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基金项目: 辽宁省自然基金面上项目(2019-ZD-0354). |
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Research and Design of Prospect Forecast System of University Scientific Research Projects based on Neural Network |
WANG Hanyuan, JIANG Ying
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(Software Engineering Department, Dalian Neusoft Institute of Information, Dalian 116023, China )
wanghanyuan16@dnui.edu.cn; jiangying@neusoft.edu.cn
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Abstract: This paper proposes to build a reliable prospect forecast system for scientific research projects in order to effectively predict prospects of scientific research projects in universities and further improve conversion rate of scientific research results. The system is based on neural networks and a network platform shared by scientific research projects. A model is generated by parameterizing characteristics of a large number of various scientific research projects, using the non-linear mapping ability, adaptive ability and generalization ability of BP (Back Propagation) neural network. Then, the model is used for reliable forecast of a new project from multiple dimensions. Experiments show that the prediction results, produced by the BP neural network algorithm after learning a large number of pre-processed samples, have high accuracy, and can be updated and adapted with new sample input. Therefore, this method is highly feasible. |
Keywords: university scientific research projects; prospect prediction; neural network |